2026-05-02 10:33:05
Last week, we went over Marvel Comics’ subscription service, Marvel Unlimited. So, it would only be fair to check out DC’s subscription service: DC Universe Infinite. They’re pretty similar; if you use one, you can navigate and understand the other. There are some key differences, though, enough to warrant a whole separate article. Here’s what you need to know about DC Universe Infinite.
The subscription service has 3 different plans, each with different content. Let’s go over what each plan has and how much they cost.
The first plan is completely free, so it should come as no surprise that this is the plan with the least amount of content. But you do get some neat stuff. You get a few free comic books to read, and these change from time to time. You also get some comics from their DC GO! imprint. This imprint is specifically made to be read on digital devices. Not bad for a free tier.
Next is the standard plan. This plan can be bought monthly for $7.99 or annually for $74.99. According to the DC Universe Infinite website, here’s everything that comes with this plan: over 27k comics, with new comic books being available 6 months after their release. It’s a bit of a wait, but it could be worse; it could be 8 months or even a year. This plan also allows for a 7-day free trial.
The final plan is Ultra. The website states that this plan has over 35k comics, which include books from imprints such as Vertigo and Black Label. Also, instead of waiting 6 months for new releases, you’ll now have to wait just 30 days. This plan is definitely the one with the most value, but it’s also the priciest. Monthly is $12.99, and annually is $119.99. A 7-day free trial is also available for this plan.
\ These are the 3 plans that potential customers can choose from. Now, let’s take a look at what devices are supported.
In the FAQ section of the website, it says that it’s available on iPhones, iPads, Android phones, and Android tablets. You might notice that there’s one big omission: Amazon Kindle tablets. Yep, like Marvel Unlimited, this service is also not available on these devices. It’s unfortunate, but not a dealbreaker.
\ I’ve personally used this service on iPhone and iPad, and it worked seamlessly. I haven’t tried it on Android devices, but I imagine it would be a similar positive experience.
\ Now, for 2 more important questions:
I would say yes, it’s absolutely worth it. If you’re just a casual DC fan and want to read certain comics from time to time, I would go for the standard plan. If you love reading comics and know you can read a ton in a month, the Ultra plan is the one for you. And whether you want to go monthly or annually is up to you. It’s apparently 23% cheaper to go annually.
\ However, I also know that some people love to alternate between services. One month, it would be Marvel Unlimited, then DC Universe Infinite. I think this might be the smartest way to do it, but there is no right or wrong way. So, choose the right option for you, and start reading!
\
2026-05-02 10:00:41
The science of using computer programs to sift through thousands of data points and then using computer programs to present that data in a visual format.
In 2022, Gartner named Microsoft Power BI the Business Intelligence and Analytics Platforms leader. These are the 13 Best Datasets for Power BI Practice.
3 ways to pull JSON data into a Google Spreadsheet
Mobile phones have always been a staple of corporate communication. In the early days, companies would provide mobile devices to their employees.
Today I'm open sourcing "Grid studio", a web-based spreadsheet application with full integration of the Python programming language.
Classification algorithms learn how to assign class labels to examples (observations or data points), although their decisions can appear opaque.
This story looks into random forest regression in R, focusing on understanding the output and variable importance.
There can be one or many solutions to a given problem, depending on the scenario, As there can be many ways to solve that problem. Think about how do you approach a problem. Lets say you need to do something straight forward like a math multiplication. Clearly there is one correct solution, but many algorithms to multiply, depending on the size of the input. Now, take a more complicated problem, like playing a game(imagine your favorite game, chess, poker, call of duty, DOTA, anything..). In most of these games, at a given point in time, you have multiple moves that you can make, and you choose the one that gives you best possible outcome. In this scenario, there is no one correct solution, but there is a best possible solution, depending on what you want to achieve. Also, there are multiple ways to approach the problem, based on what strategy you choose to have for your game play.
A typical interview process for a data science position includes multiple rounds. Often, one of such rounds covers theoretical concepts, where the goal is to determine if the candidate knows the fundamentals of machine learning.
The theory formulates a mathematical model to optimize the asset allocations to gain the maximum return for a given risk-level.
In this listicle, you'll find some of the best data engineering courses, and career paths that can help you jumpstart your data engineering journey!
In order to understand how a certain metric varies over time and to predict future values, we will look at the 10 Best Datasets for Time Series Analysis.
Topic modeling is an unsupervised machine learning technique that can automatically identify different topics present in a document (textual data). Data has become a key asset/tool to run many businesses around the world. With topic modeling, you can collect unstructured datasets, analyzing the documents, and obtain the relevant and desired information that can assist you in making a better decision.
On my self-taught programming journey, my interests lie within machine learning (ML) and artificial intelligence (AI), and the language I’ve chosen to master is Python.
We will focus on MSE and MAE metrics, which are frequently used model evaluation metrics in regression models.
Learn how to save time and eliminate manual data imports in Google Sheets by automatically connecting and importing data from external sources.
Image annotation is one of the most important tasks in computer vision. With numerous applications, computer vision essentially strives to give a machine eyes – the ability to see and interpret the world. At times, machine learning projects seem to unlock futuristic technology we never thought possible. AI-powered applications like augmented reality, automatic speech recognition, and neural machine translation have the potential to change lives and businesses around the world. Likewise, the technologies that computer vision can give us (autonomous vehicles, facial recognition, unmanned drones) are extraordinary.
Ever since Google Web Search API deprecation in 2011, I've been searching for an alternative. I need a way to get links from Google search into my Python script. So I made my own, and here is a quick guide on scraping Google searches with requests and Beautiful Soup.
There are multiple approaches that you might take to create Artificial Intelligence, based on what we hope to achieve with it and how will we measure its success. It ranges from extremely rare and complex systems, like self driving cars and robotics, to something that is a part of our daily lives, like face recognition, machine translation and email classification.
Feature Selection in python is the process where you automatically or manually select the features in the dataset that contribute most to your prediction.
Importance of C++ in Data Science and Big Data
Learn how to easily extract valuable information from Google Maps using Python with our step-by-step guide.
Computer vision enables computers to understand the content of images and videos. The goal in computer vision is to automate tasks that the human visual system can do.
In a real-world setting, you often only have a small dataset to work with. Models trained on a small number of observations tend to overfit and produce inaccurate results. Learn how to avoid overfitting and get accurate predictions even if available data is scarce.
Big data may seem like any other buzzword in business, but it’s important to understand how big data benefits a company and how it’s limited.
Facial recognition-based authentication to verify a user in a web application is discussed in a beginner-friendly manner using FaceIO APIs.
Google Colab and VS Code are popular editor tools. Learn how you can use Google Colab with VS Code and take advantage of a full-fledged code editor.
RAIN executives give a full breakdown of the build out and power of AI Voice Assistants.
As if taking a picture wasn’t a challenging enough technological prowess, we are now doing the opposite: modeling the world from pictures. I’ve covered amazing AI-based models that could take images and turn them into high-quality scenes. A challenging task that consists of taking a few images in the 2-dimensional picture world to create how the object or person would look in the real world.
We’re going to use Term Frequency — Inverse Document Frequency (TF-IDF) to find the most important sentences in a BBC news article. Then we are going to implement this algorithm into a quick & easy Firefox extension.
Hello, Machine Learning community!
There're numerous JavaScript charting libraries. To make your life easier, I decided to share my picks. Check out the best JS libraries for creating web charts!
The Datasets library from hugging Face provides a very efficient way to load and process NLP datasets from raw files or in-memory data. These NLP datasets have been shared by different research and practitioner communities across the world.
A curated list of courses to learn data science, machine learning, and deep learning fundamentals.
Text classification datasets are used to categorize natural language texts according to content. For example, think classifying news articles by topic, or classifying book reviews based on a positive or negative response. Text classification is also helpful for language detection, organizing customer feedback, and fraud detection. Though time consuming when done manually, this process can be automated with machine learning models. The result saves companies time while also providing valuable data insights.
The 2019–20 coronavirus pandemic is an ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak was first identified in Wuhan, Hubei, China, in December 2019, and was recognized as a pandemic by the World Health Organization (WHO) on 11 March 2020.
While the release of GPT-3 marks a significant milestone in the development of AI, the path forward is still obscure. There are still certain limitations to the technology today. Here are six of the major limitations facing data scientists today.
Data is very important in building computer vision models and these are the 10 Biggest Datasets for Computer Vision.
Data is a central piece of the climate change debate. With the climate change datasets on this list, many data scientists have created visualizations and models to measure and track the change in surface temperatures, sea ice levels, and more. Many of these datasets have been made public to allow people to contribute and add valuable insight into the way the climate is changing and its causes.
On Hacker Noon, I will be sharing some of my best-performing machine learning articles. This listicle on datasets built for regression or linear regression tasks has been upvoted many times on Reddit and reshared dozens of times on various social media platforms. I hope Hacker Noon data scientists find it useful as well!
A data science interview consists of multiple rounds. One of such rounds involves theoretical questions, which we covered previously in 160+ Data Science Interview Questions.
Learn to build AI ruled-based chatbot with a simple tutorial that can be showcased in your Portfolio.
How I learned to stop using pandas and love SQL.
This blog post explains the most intricate data warehouse SQL techniques in detail.
Here’s DreamFusion, a new Google Research model that can understand a sentence enough to generate a 3D model of it.
Dummy data is randomly generated data that can be substituted for live data. Whether you are a Developer, Software Engineer, or Data Scientist, sometimes you need dummy data to test what you have built, it can be a web app, mobile app, or machine learning model.
A Quick Method To Extract Tweets and Replies For Free
Best stock market data APIs for data scientists and algorithmic traders: Alpha Vantage, Barchart OnDemand, Tradier, Intrinio, and Xignite.
For those looking to build predictive models, this article will introduce 10 stock market and cryptocurrency datasets for machine learning.
Processing large data, e.g. for cleansing, aggregation or filtering is done blazingly fast with the Polars data frame library in python thanks to its design.
Early January 2022, I spontaneously bought a pager. I looked into the US pager market, and to my surprise…
Get savvy with Pandas DataFrame updates & appends using dictionaries for smoother data tinkering.
AI is being used to help analysts with routine tasks. But it can also be a real contender on the analytics team.
Spark is the name of the engine to realize cluster computing while PySpark is the Python's library to use Spark.
While I'm usually a JavaScript person, there are plenty of things that Python makes easier to do. Doing voice recognition with machine learning is one of those.
Learn how to execute web scraping on Twitter using the snsscrape Python library and store scraped data automatically in database by using HarperDB.
Multicollinearity refers to the high correlation between two or more explanatory variables, i.e. predictors. It can be an issue in machine learning too.
pandas and matplotlib.
Recently I had to write a script, which should’ve changed some JSON data structure in a PSQL database. Here are some tricks I learned along the way.
An Introduction to Anomaly Detection and Its Importance in Machine Learning
Explore the intricacies of calculating median statistics in sliding windows, a vital tool for real-time data analysis in diverse fields.
Let's conduct a penetration testing on a file with a detailed study analysis of system passwords as part of an ethical hacking engagement.
Explore the evolution of DataOps in data engineering, its parallels with DevOps, challenges it addresses, and best practices. Transformative future of DataOps.
There was a time when the data analyst on the team was the person driving digitalization in an adventurous data quest…and then the engineers took over.
Linear Regression is generally classified into two types:
Motivation
To scrape a website, it’s common to send GET requests, but it's useful to know how to send data. In this article, we'll see how to start with POST requests.
Drowsiness detection is a safety technology that can prevent accidents that are caused by drivers who fell asleep while driving.
Performant machine learning models require high-quality data. And training your machine learning model is not a single, finite stage in your process. Even after you deploy it in a production environment, it’s likely you will need a steady stream of new training data to ensure your model’s predictive accuracy over time.
Here are the Top 9 ML, AI, and Data Science Internships to consider for 2022 if you want to get into any of these very lucrative fields in computer science.
Web apps are still useful tools for data scientists to present their data science projects to the users. Since we may not have web development skills, we can use open-source python libraries like Streamlit to easily develop web apps in a short time.
When you absolutely need to have a perfect replica of your data for data exploration, CockroachDB and MinIO is your winning strategy.
Karate Club is an unsupervised machine learning extension library for the NetworkX Python package. See the documentation here.
Today, with open source machine learning software libraries such as TensorFlow, Keras or PyTorch we can create neural network, even with a high structural complexity, with just a few lines of code. Having said that, the Math behind neural networks is still a mystery to some of us and having the Math knowledge behind neural networks and deep learning can help us understand what’s happening inside a neural network. It is also helpful in architecture selection, fine-tuning of Deep Learning models, hyperparameters tuning and optimization.
The README file is the very first item that developers examine when they access your Data Science project hosted on GitHub. Every developer should begin their exploration of your Data Science project by reading the README file. This will tell them everything they need to know, including how to install and use your project, how to contribute (if they have suggestions for improvement), and everything else.
A big question for Machine Learning and Deep Learning apps developers is whether or not to use a computer with a GPU, after all, GPUs are still very expensive. To get an idea, see the price of a typical GPU for processing AI in Brazil costs between US $ 1,000.00 and US $ 7,000.00 (or more).
Whether you’re a beginner looking for introductory articles or an intermediate looking for datasets or papers about new AI models, this list of machine learning resources has something for everyone interested in or working in data science. In this article, we will introduce guides, papers, tools and datasets for both computer vision and natural language processing.
For the first KDnuggets post on Hacker Noon, we bring you a lighter fare of very nerdy computer humor from the series of self-referential jokes started on Twitter earlier this week. Here are some of our favorites.
If you do understand all of the jokes, then you congratulate yourself on having excellent knowledge of Data Science and Machine Learning! If you have actually laughed at 2 or more jokes, then you have earned MS in Computer Humor! If you just smirked, you probably have a Ph.D. And I have a great joke about AGI, but it will be ready in 10 years.
Enjoy, and if you have more, add them in comments below!
Yann LeCun, @ylecun
Although commonplace, logs hold critical information about system operations and are a valuable source of debugging and troubleshooting information.
In this tutorial, I will guide you on how to detect emotions associated with textual data and how can you apply it in real-world applications.
MinIO is a high-performance, cloud native object store. Because of this, MinIO can become the global datastore for Snowflake customers, wherever their data sits
More recently on my data science journey I have been using a low grade consumer GPU (NVIDIA GeForce 1060) to accomplish things that were previously only realistically capable on a cluster - here is why I think this is the direction data science will go in the next 5 years.
Data analytics can transform how businesses operate. With companies having tons of data today , data analytics can help companies deliver valuable products and services to customers.
In Reinforcement Learning (RL), agents are trained on a reward and punishment mechanism. The agent is rewarded for correct moves and punished for the wrong ones. In doing so, the agent tries to minimize wrong moves and maximize the right ones.
True story from retail finance about LTV modeling with ML algorithms for evaluation customer acquisition channels.
MinIO is the right choice for Quickwit because of its industry-leading performance and scalability.
After reading this article, you will be able to create a search engine for similar images for your objective from scratch
Learn how to approach data-driven measurement properly. See what unexpected results we got in a bank and get insights for your own data analytics journey.
Hugging Face offers solutions and tools for developers and researchers. This article looks at the Best Hugging Face Datasets for Building NLP Models.
This post focuses on how Iceberg and MinIO complement each other and how various analytic frameworks (Spark, Flink, Trino, Dremio, Snowflake) can leverage them.
The combination of MinIO and Delta Lake enables enterprises to have a multi-cloud data lake that serves as a consolidated single source of truth.
From no limits on unstructured data to having greater control over serving models, here are some reasons why AI is built on object storage.
Streamlit, Dash, Reflex and Rio. A comparison of python web app frameworks .
We’ve all heard about GPT-3 and have somewhat of a clear idea of its capabilities. You’ve most certainly seen some applications born strictly due to this model, some of which I covered in a previous video about the model. GPT-3 is a model developed by OpenAI that you can access through a paid API but have no access to the model itself.
Web scraping has broken the barriers of programming and can now be done in a much simpler and easier manner without using a single line of code.
To help you build object recognition models, scene recognition models, and more, we’ve compiled a list of the best image classification datasets. These datasets vary in scope and magnitude and can suit a variety of use cases. Furthermore, the datasets have been divided into the following categories: medical imaging, agriculture & scene recognition, and others.
Metabase is a business intelligence tool for your organisation that plugs in various data-sources so you can explore data and build dashboards. I'll aim to provide a series of articles on provisioning and building this out for your organisation. This article is about getting up and running quickly.
You will find out how we at inDrive currently handle regular vehicle verifications. Every month, we ask our users to take a picture of their car.
When you think of Artificial Intelligence, the first thing that comes to mind is either Robots or Machines with Brains or Matrix or Terminator or Ex Machina or any of the other amazing concepts having machines that can think. This is an appropriate but vague understanding of Artificial Intelligence. In this article we’ll see what A.I. really is and how the definition has changed in the past.
Researchers have been studying the possibilities of giving machines the ability to distinguish and identify objects through vision for years now. This particular domain, called Computer Vision or CV, has a wide range of modern-day applications.
Using MinIO for Hudi storage paves the way for multi-cloud data lakes and analytics.
Dashboard with different visualizations allows you to compare data and show changes and tendencies. In this tutorial I wil explain why and how to build one.
As an aspiring data scientist, the best way for you to increase your skill level is by practicing. And what better way is there for practicing your technical skills than making projects.
If you've been on LinkedIn anytime in the past several months, you've probably come across the infamous "certification post."
In my free time, I am attempting to build my own smart home devices. One feature they will need is speech recognition. While I am not certain yet as to how exactly I want to implement that feature, I thought it would be interesting to dive in and explore different options. The first I wanted to try was the SpeechRecognition library.
Learn about ColBERT, a new way of scoring passage relevance using a BERT language model that substantially solves the problems with dense passage retrieval.
Looking for MongoDB data visualization tool? There are plenty of options but firstly its better to explore what kinds of solutions there are on the market.
Every business has its goals and the path to attaining those goals usually lies in data, it’s why our data is so important today.
You have a plain old TensorFlow model that’s too computationally expensive to train on your standard-issue work laptop. I get it. I’ve been there too, and if I’m being honest, seeing my laptop crash twice in a row after trying to train a model on it is painful to watch.
RNN is one of the popular neural networks that is commonly used to solve natural language processing tasks.
The OLAP experience of an automobile manufacturer.
Master key time series feature engineering techniques to enhance predictive models in finance, healthcare & more with our comprehensive guide.
Pynecone is an open-source framework to build web apps in pure Python and deploy with a single command.
Looking for sentiment analysis companies or sentiment annotation tools? If so, you’ve come to the right place. This guide will briefly explain what sentiment analysis is, and introduce companies that provide sentiment annotation tools and services.
Gato from DeepMind was just published! It is a single transformer that can play Atari games, caption images, chat with people, control a real robotic arm, and more! Indeed, it is trained once and uses the same weights to achieve all those tasks. And as per Deepmind, this is not only a transformer but also an agent. This is what happens when you mix Transformers with progress on multi-task reinforcement learning agents.
With the help of SystemD and MinIO you can automate your cloud object storage deployments and ensure the service lifecycle is managed smoothly and successfully.
Building a production-grade RAG application demands a suitable data infrastructure to store, version, process, evaluate, and query chunks of data.
Douglas Crockford and Chip Morngingstar created the data exchange format that is now known as JSON.
HOG - Histogram of Oriented Gradients (histogram of oriented gradients) is an image descriptor format, capable of summarizing the main characteristics of an image, such as faces for example, allowing comparison with similar images.
For those looking to analyze crime rates or trends over a specific area or time period, we have compiled a list of the 16 best crime datasets made available for public use.
It is often very difficult for AI researchers to gather social media data for machine learning. Luckily, one free and accessible source of SNS data is Twitter.
Recently, Amazon released a new tool, called Honeycode, which lets customers quickly build mobile and web applications — with no coding required. This came a few months after Google’s acquisition of the no-code mobile-app-building platform, AppSheet. While these moves surprised many, they’re in line with a larger trend I’ve observed, one that’s growing strong in all sectors, even amidst economic turmoil.
Hypothesis tests are significant for evaluating answers to questions concerning samples of data.
Counts are everywhere, so no matter your background, these data distributions will come in handy.
Machine learning models are usually developed in a training environment (online or offline). And you can then deploy them and use them with live data.
Unlock the power of AI with these 9 free tools! Boost productivity, improve decision-making, & enhance your personal life.
Transformer models have become the defacto standard for NLP tasks. As an example, I’m sure you’ve already seen the awesome GPT3 Transformer demos and articles detailing how much time and money it took to train.
How does the ZIP format work?
In Digital Healthcare data platforms, data quality is no longer a nice-to-have — it is a hard requirement.
Using ML to analyze and predict CLV offers more accurate, actionable insights by learning from behavioral data at scale.
Human behaviour describes how people interact and in this article, we will look at the 8 Best Human Behaviour Datasets for Machine Learning.
Learn how to build an NLP model and deploy it with a fast web framework for building APIs called FastAPI.
Having fun while developing is necessary for programmers and developers. No matter how much serious or tough the situation is, one should always take things lightly when it comes to software development.
A complete setup of a ML project using version control (also for data with DVC), experiment tracking, data checks with deepchecks and GitHub Action
Semi-supervised learning is the type of machine learning that is not commonly talked about by data science and machine learning practitioners but still has a very important role to play.
What is Linear Regression ?
A quick walkthrough of the three frameworks in probability viz. classical, frequentist and Bayesian through an example.
Is graph really the new star schema? What do graphs like to non-insiders, and what attracts them to the community, methodologies, applications, and innovation?
If you want to learn Microsoft Excel, a productivity tool for IT professionals, and looking for free online courses, then you have come to the right place.
Here are the top 20 Coursera Courses and Certifications to Learn Data Science, Cloud Computing, and Python.
Is Astronomy data science?
Access to training data is one of the largest blockers for many machine learning projects. Luckily, for various different projects, we can use data augmentation to increase the size of our training data many times over.
A practical guide to using machine learning in business, from defining problems and choosing models to deployment, monitoring, and delivering real value.
This is actually an assignment from Jeremy Howard’s fast.ai course, lesson 5. I’ve showcased how easy it is to build a Convolutional Neural Networks from scratch using PyTorch. Today, let’s try to delve down even deeper and see if we could write our own nn.Linear module. Why waste your time writing your own PyTorch module while it’s already been written by the devs over at Facebook?
This paper talks to the rise and fall of Hadoop HDFS and why high-performance object storage is a natural successor in the big data world.
A deep dive into 5 early adopters of vector search- Pinterest, Spotify, eBay, Airbnb and Doordash- who have integrated AI into their applications.
Researchers use an algebraic acme called “Losses” in order to optimise the machine learning space defined by a specific use case.
In version 3.2.0, DolphinScheduler introduces a series of new features and improvements, significantly enhancing its stability.
Scientists use geospatial analytics to build visualizations such as maps, graphs and cartograms. These are the Best Public Datasets for Geospatial Analytics.
Research suggests that data scientists spend a whopping 80% of their time preprocessing data and only 20% on actually building machine learning models. With that in mind, it’s no wonder why the machine learning community was quick to embrace crowdsourcing for data labeling. Crowdsourcing helps break down large and complex machine learning problems into smaller and simpler tasks for a large distributed workforce.
In the process of building a Machine Learning model, there is a trade-off between bias and variance.
Andrew Ng likes it, you probably will too!
DynamoDB's secondary indexes are a powerful tool for enabling new access patterns for your data.
Explore time series analysis: from cross-validation, decomposition, transformation to advanced modeling with ARIMA, Neural Networks, and more.
We, humans, are experiencing tailor-made services which have been engineered right for us, we are not troubled personally, but we are doing one thing every day, which is kind of helping this intelligent machine work day and night just to make sure all these services are curated right and delivered to us in the manner we like to consume it.
In this tutorial, we will develop a simple Agent that accesses multiple data sources and invokes data retrieval when needed.
Malloy is a new experimental language for describing data relationships and transformations created by the developer of Looker.
For analytical use cases, you can gain significant performance and cost advantages by syncing the DynamoDB table with a different tool or service like Rockset.
This guide will look into the ten best B2B data providers that can fuel your business strategy and help you expand your customer base.
Product manager interviews usually include a section on metrics. As a data scientist at Uber, I’ve often given or helped friends prepare for these interviews. The difference between candidates who crush the metric questions and those who struggle turns, as far as I can tell, on whether they have a framework that they can apply.
Binary classification is one of the most common machine learning tasks. In practice, the goal of such tasks often extends beyond simply predicting a class.
How to use Approximate leave-one-out cross-validation for hyperparameter optimization and outlier detection for logistic regression and ridge regression
Tree-based models like Random Forest and XGBoost have become very popular in solving tabular(structured) data problems and gained a lot of tractions in Kaggle competitions lately. It has its very deserving reasons. However, in this article, I want to introduce a different approach from fast.ai’s Tabular module leveraging.
Learn how to combine categorical features in your dataset to improve your machine learning model performance.
This article is a quick introduction to Dagster using a small ML project. It is beginner friendly but might also suit more advanced programmers if they dont know Dagster.
Is your Brain a Data Scientist? Yes, according to the Bayesian Brain Hypothesis, your brain is a Bayesian statistician. Let me explain.
Learn how machine learning advances product analytics — from predicting behavior to optimizing personalized, data-driven decisions.
As we sit down for this exclusive interview, Leonid offers a rare glimpse into the intricate process of weaving the digital fabric that shapes our lives.
Hi folks !! In this post, i will discuss about basic tools and software that one can use to solve a data science problem . If you are new to ML or Data Science or Statistics, Feel free to check out my other blog on ML by clicking on the link below.
Exploratory Data Analysis (EDA) is an essential step in the data science project lifecycle. Here are the top 10 python tools for EDA.
Learn 5 ways to accelerate point queries and 4 methods to further improve concurrency: row storage format, short circuit, prepared statement, and row storage ca
How can we know ours ads are making impact that we aim for? What if targeted ads are not working the way we want them to?
Transformer models have become by far the state of the art in NLP technology, with applications ranging from NER, Text Classification, and Question Answering
We are living in a weird time. Day by day we see more & more people coughing and getting sick, our neighbors, coworkers on Zoom calls, politicians, etc… But here’s when it becomes really, really scary — when you become one of “those” and have no clue what to do. Your reptile brain activates, you enter a state of panic, and engage complete freakout mode. That’s what happened to me this Monday, and I’m not sure I’m past this stage.
Learn how to use MySQL’s SET and ENUM data types effectively. This guide explains their internal behavior, common pitfalls, and best practices
Collecting data from the web can be the core of data science. In this article, we'll see how to start with scraping with or without having to write code.
Have you heard of the data Streamhouse yet? Find out more and learn about Apache Paimon
Everyone is talking about ontologies. Why, what is an ontology actually, and how is it related to graphs?
Pull stock prices from online API and perform predictions using Recurrent Neural Network & Long Short Term Memory (LSTM) with TensorFlow.js framework
So you want to become a data scientist? You have heard so much about data science and want to know what all the hype is about? Well, you have come to the perfect place. The field of data science has evolved significantly in the past decade. Today there are multiple ways to jump into the field and become a data scientist. Not all of them need you to have a fancy degree either. So let’s get started!
How to not get stuck when collecting tabular data from the internet.
Exploring Data Science and Machine Learning (DSML) Platforms
How does the GIF format work?
Explore a product developer's journey in tackling AI bias and fairness. Learn how ethical considerations shape AI design, ensuring technology benefits everyone.
This blog explains about polygon data, its benefits and how it is widely used in geomarketing, indoor mapping, and mobility analysis for orgnaizations.
Google recently announced a new model for automatically generating summaries using machine learning, released in Google Docs that you can already use.
An incredible 87% of data science projects never go live.
PyTorch has gained a reputation as a research-focused framework, and these are the Best PyTorch Datasets for Building Deep Learning Models available today.
CRISPR, Quantum, Graphene, Smart Dust, Digital Twins, the Metaverse… You’ve heard about it all. Seen it all. Read it all. Or have you?
In this article, we set sail on a captivating journey through the EDA process, using the legendary Titanic dataset from Kaggle as our North Star.
In this blog, you will learn about the Pickling and Unpickling process, although it is quite simple it is very important and useful.
Here are the five best articles related to artificial intelligence in May posted on Hackernoon.
Uploading 1 million row size large CSV to mongoDB using nodejs stream
An introduction to neural vector search, in comparison to keyword-based search.
Intro
Let’s build a fashion-MNIST CNN, PyTorch style. This is A Line-by-line guide on how to structure a PyTorch ML project from scratch using Google Colab and TensorBoard
Qlik Sense is powerful data visualization and BI software. But sometimes its functions are not enough. Meet the best Qlik Sense extensions to do more with data!
The online data science community is supportive and collaborative. One of the ways you can join the community is to find machine learning and AI Slack groups.
Introduction
Ensemble modelling helps you avoid overfitting by reducing variance in the prediction and minimizing modelling method bias.
The time to start building one's synthetic replacement is now.
Minimalistic Data Structure Sketches
Programming is a complex and multifaceted field that encompasses a wide range of mathematical and computational concepts and techniques.
I am a huge fan of combat sports, with boxing in particular being my favourite. As much as it may appear as a purely physical sport where your sole objective is to either outbox or knock your opponent out, it is far more strategic that one would expect and incorporates an element psychology. Like a chess game, each punch thrown has to be calculated, recklessly overextending yourself might leave you more vulnerable to a counter punch, while being overly passive and defensive might swing the momentum in your opponent’s favour and not get you enough points to win the fight. If you let self-doubt sink in or are intimidated by your opponent you have already lost the battle. On top of all this, you need to remain respectful of the sport and the life threatening dangers it presents. In the words of of Sugar Ray Leonard, 'you don't play boxing'.
Pycaret is an open-source, low code library in python that aims to automate the development of machine learning models.
This headline may seem a bit odd to you. After all, if you’re a data scientist in 2019, you’re already marketable. Since data science has a huge impact on today’s businesses, the demand for DS experts is growing. At the moment I’m writing this, there are 144,527 data science jobs on LinkedIn alone.
Gain entry into IT with knowledge of data science, engineering, cloud computing, cybersecurity, or devops.
Attacking Toxic Comments Kaggle Competition Using Fast.ai
Marketing Mix Modeling is a statistical analysis method used in marketing to determine the optimal allocation of resources.
How tech executives can harness advanced econometric and AI-driven simulation techniques to make informed investment decisions under uncertainty?
When it comes to building an Artificially Intelligent (AI) application, your approach must be data first, not application first.
Imagine — You’re in a system design interview and need to pick a database to store, let’s say, order-related data in an e-commerce system. Your data is structured and needs to be consistent, but your query pattern doesn’t match with a standard relational DB’s. You need your transactions to be isolated, and atomic and all things ACID… But OMG it needs to scale infinitely like Cassandra!! So how would you decide what storage solution to choose? Well, let’s see!
There exist two common log processing solutions within the industry, exemplified by Elasticsearch and Grafana Loki, respectively.
DecentraMind by Web 3.0 or for it? — interview with Mikhail Danieli, project visionary and ambassador about the future of the platform and the company.
Machine learning has become a diverse business tool to enhance the various elements of business operations. Also, it has a significant influence on the performance of the business. Machine learning algorithms are used widely to maintain competition with different industries. However, there is a different type of algorithms for goals and data sets. The selection of an algorithm depends on user role and the purpose. If you are using Linear regression, then you can quickly implement or train rather than other machine learning algorithms. But the drawback of this algorithm is that it is not applicable for complex predictions. So you should know about the different types of machine learning algorithms for getting better results.
In this article, we will learn about GNNs and its structure as well as its applications
Comprehensive walkthrough on using CocoIndex to build unified, incrementally updated search and analytics pipelines.
Privacy](https://hackernoon.com/differential-privacy-with-tensorflow-20-multi-class-text-classification-privacy-yk7a37uh)
Introduction
Here’s the full list of top AI conferences to attend in 2022, from the most technical to business-focused to academic
After noticing my programming courses in college were outdated, I began this year by dropping out of college to teach myself machine learning and artificial intelligence using online resources. With no experience in tech, no previous degrees, here is the degree I designed in Machine Learning and Artificial Intelligence from beginning to end to get me to my goal — to become a well-rounded machine learning and AI engineer.
Learn how to build an NLP model and deploy it with a fast web framework for building APIs called FastAPI.
Machine learning models are often developed in a training environment, which may be online or offline, and can then be deployed to be used with live data once they have been tested.
The question of from-scratch implementation vs Python library comes up once in a while, no matter the goal of your project.
Prices move in a wave like fashion, moving back and forth following a broader trend. While doing so, it often revolves around a mean. It might move across or bounce off the mean. Mean reversion systems are designed to exploit this tendency.
Too lazy to scrape nlp data yourself? In this post, I’ll show you a quick way to scrape NLP datasets using Youtube and Python.
Why average ROI fails. Learn how distributional and tail-risk modeling protects marketing campaigns from catastrophic losses using Bayesian methods.
In machine learning, each type of artificial neural network is tailored to certain tasks. This article will introduce two types of neural networks: convolutional neural networks (CNN) and recurrent neural networks (RNN). Using popular Youtube videos and visual aids, we will explain the difference between CNN and RNN and how they are used in computer vision and natural language processing.
You've most certainly seen movies like the recent Captain Marvel or Gemini Man where Samuel L Jackson and Will Smith appeared to look like they were much younger. This requires hundreds if not thousands of hours of work from professionals manually editing the scenes he appeared in. Instead, you could use a simple AI and do it within a few minutes.
Getting actionable insights around a topic using the new Twitter API v2 endpoint
The article explores Machine Learning's vital role in cybersecurity, addressing evolving digital threats. It covers ML's types, iterative process, feature engi
As part of my data-science career track bootcamp, I had to complete a few personal capstones. For this particular capstone, I opted to focus on building something I personally care about - what better way to learn and possibly build something valuable than by working on a passion project.
I always wanted to learn programming. Writing codes, making algorithms always excited me. Being a mechanical engineer, I was never taught these subjects in depth.
In this article, we cover how to use pipeline patterns in python data engineering projects. Create a functional pipeline, install fastcore, and other steps.
We human beings are depending so much on digital and smart devices. And all these devices are creating data at a very fast rate. According to an article on Forbes more than 90% of the world data has been created in past 2 to 3 years.
With each day, enterprises increasingly rely on data to make decisions.
Comparative Study of Different Adversarial Text to Image Methods
See how Andrei Shcherbinin built production-ready ML systems with 12x faster attribution, 95% chatbot automation, and stronger monitoring.
Another clever tool for a powerful SQL pre-processor
A Must-know for AI Enthusiasts](https://hackernoon.com/diverse-types-of-artificial-intelligence-a-must-know-for-ai-enthusiasts)
A precursory article that explains various categorizations of artificial intelligence, some real-life examples and concepts.
Using Relational Database to search inside unstructured data
This article will serve as a lesson on the shocking reasons for your AI adoption disaster. We see news about machine learning everywhere. Indeed, there is lot of potential in machine learning. According to Gartner’s predictions, “Through 2020, 80% of AI projects will remain alchemy, run by wizards whose talents will not scale in the organization” and Transform 2019 of VentureBeat predicted that 87% of AI projects will never make it into production.
Why you should prepare for BI analyst interview questions?
A beginner’s guide to Probability and Random Events. Understand the key statistics concepts and areas to focus on to ace your next data science interview.
We get a glimpse into the inner workings of a valuable company and it turns out it's not all sunshine and rainbows.
Universal Approximation Theorem says that Feed-Forward Neural Network (also known as Multi-layered Network of Neurons) can act as powerful approximation to learn the non-linear relationship between the input and output. But the problem with the Feed-Forward Neural Network is that the network is prone to over-fitting due to the presence of many parameters within the network to learn.
In this post, I wanted to share a Reddit dataset list that gained a lot of traction on social media when it was first posted.
Google makes billions and billions from paid search, but did you know those folks without adblockers are only responsible for about 6 percent of web visits? Long live free organic search, the primary diet for almost 2/3rds of all web traffic!
You can easily build a personal AI chatbot that runs both online (using OpenAI GPT) and offline (using Ollama local models) right from your local machine.
Handwriting Recognition:
Discover the key differences between MLOps Engineer vs ML Engineer roles, including focus, collaboration, and tooling.
What are context graphs, what are they good for, and why are they dubbed AI’s trillion-dollar opportunity? What does context mean, and how can it be defined?
Learn how to apply a variety of techniques to select features with Xverse package.
I unknowingly blew $3,000 in 6 hours on one query in Google Cloud BigQuery. Here’s why and 3 easy steps to optimize the cost.
Retraining Machine Learning Model, Model Drift, Different ways to identify model drift, Performance Degradation
The hype around AI is growing rapidly, as most research companies predict AI will take on an increasingly important role in the future.
In these difficult days for all of us, I’ve heard all sorts of things. From the fake news sent through Whatsapp, like vitamin C can save your life, to holding your breath in the morning to check if you’ve been hit by COVID-19. The mantra that everyone keeps repeating is “stay at home!”, okay fine, but what exactly does “stay home” mean? The question seems ridiculous when you think of a relatively short period, 15 days? A month? But if we look critically at the situation, we surely realize that it won’t be 15 days, and it won’t be a month. It will be a long, long time. Why am I saying this? Because “stay at home” doesn’t protect us from the virus. Staying at home is to protect our health care facilities from collapse. And I’m not saying that this is wrong. I’m just saying that if we want to protect the health care system from collapse, well then we’ll stay home a long, long time. But in doing so we will irreparably damage the economic system by profoundly changing our social and political model. It is inevitable. Let’s face it and not have too many illusions.
Comprehensive List of Feature Store Architectures for Data Scientists and Big Data Professionals
Here is a list of the best books to learn machine learning for beginners to help build their careers in the ML Industry.
For years AI was touted to be the next big technology. Expected to revolutionize the job industry and effectively kill millions of human jobs, it became the poster child for job cuts. Despite this, its adoption has been increasingly well-received. To the tech experts, this wasn’t really surprising given its vast range of use cases.
Search Engine Optimization (SEO) has been the backbone of an online search for over two decades now. But as Artificial Intelligence (AI) technology moves quickl
Explore the nuances of MySQL’s DATETIME and TIMESTAMP types, from handling time zones and zero dates to optimizing performance and preventing pitfalls.
An article explaining the intuition behind the “positional embedding” in transformer models from the renowned research paper - “Attention Is All You Need”.
Do we need a radical new approach to data warehouse technology? An immutable data warehouse starts with the data consumer SLAs and pipes data in pre-modeled.
Elections play crucial role in all democracies and social media is an important aspect in this process. Presently, political parties increasingly rely on social media platforms like Twitter and Facebook for political communication.The use of social media in political marketing campaigns has grown dramatically over the past few years. It is also expected to become even more critical to future political campaigns, as it creates two-way communication and engagement that stimulates and fosters candidates relationships with their supporters.
Have you ever dreamed of a good transcription tool that would accurately understand what you say and write it down? Not like the automatic YouTube translation tools… I mean, they are good but far from perfect. Just try it out and turn the feature on for the video, and you’ll see what I’m talking about.
Artificial intelligence is changing the world as we know it. Form self-driving cars to weather predictions. Now it's taking on the stock market. Here's how.
Most data science job descriptions are actually for data engineers.
This post includes a round-up of some of the best free beginner tutorials for Machine Learning.
Discover the evolution and importance of decision trees in machine learning, from their early beginnings in the 1960s to their widespread use in modern ensemble
Want to train machine learning models on your Mac’s integrated AMD GPU or an external graphics card? Look no further than PlaidML.
We explore the use of OpenCV and techniques like contour detection for eye blink detection, pupil tracking, Discuss the challenges and their specific Solutions.
We’ve been asked if Airbyte was being built on top of Singer. Even though we loved the initial mission they had, that won’t be the case. Aibyte's data protocol will be compatible with Singer’s, so that you can easily integrate and use Singer’s taps, but our protocol will differ in many ways from theirs.
If you are a beginner and just started machine learning or even an intermediate level programmer, you might have been stuck on how do you solve this problem. Where do you start? and where do you go from here?
This week on HackerNoon's Stories of the Week, we looked at three articles that covered the world of software development from employment to security.
Learn the distinctions between AI and ML with vivid examples.
If you are a two-degree marketplace like Uber, you cater to millions of users requesting a ride through your driver partners accepting and fulfilling those requests. For a three-degree marketplace like Swiggy, there is another static component added (like restaurants or stores), where delivery partners pick up the orders.
A quick demonstration of using JavaScript to download ad hoc data.
This guide explores real-time AI and the unique performance and cost attributes of Cassandra that make it an excellent database for a feature store.
A machine learning guide on how to identify fraudulent credit card transactions by using the PyOD toolkit.
Anscombe’s quartet comprises four data sets that have nearly identical simple descriptive statistics, yet have very different distributions and appear very different when graphed.
— Wikipedia
Evolution of our data processing architecture towards better performance and simpler maintenance at Tencent Music.
This tutorial will help you get started with NumPy by teaching you to visualize multidimensional arrays.
With the cost of a cup of Starbucks and two hours of your time, you can own your own trained open-source large-scale model.
Running inference at scale is challenging. See how we speed up the I/O performance for large-scale ML/DL offline inference jobs.
Explore the fascinating world of Reinforcement Learning through Multi-Armed Bandits (MABs), balancing exploration & exploitation.
This post covers all you will need for your Journey as a Beginner. All the Resources are provided with links. You just need Time and Your dedication.
Do you know the machine learning global market is estimated to reach $30.6 billion by 2024? This marvellous growth is the outcome of Omni-presence of artificial intelligence and its trending subset; machine learning.
Let’s talk about self-supervised machine learning - a way to teach a model a lot without manual markup, as well as an opportunity to avoid deep learning when setting a model up to solve a problem. This material requires an intermediate level of preparation; there are many references to original publications.
Are you data literate? In today's data-driven world, data literacy is a crucial skill. Here's how you can develop it for yourself.
Use Monte Carlo simulation to understand the risk in fantasy baseball. Learn why optimizing a lineup is a tall order.
DJ Patil and Jeff Hammerbacher coined the title Data Scientist while working at LinkedIn and Facebook, respectively, to mean someone who “uses data to interact with the world, study it and try to come up with new things.”
A beginner level tutorial to get started with data visualization by creating an interesting and intuitive JavaScript bubble map
On November 15th, MetaAI and Papers with Code announced the release of Galactica, a game-changer, open-source large language model trained on scientific knowledge with 120 billion parameters.
From astrophysics to data science, here's a story of a lifetime journey with modeling the Universe and other dynamic things that move through space and time.
Data analysis as a whole is one of the most important industries. Now that DeFi is a full-fledged industry, there is a growing need for valuable data analytics.
Find the top 40+ product interview questions you must prepare for your next data science interview.
How Jupyter Notebooks played an important role in the incredible rise in popularity of Data Science and why they are its future.
Learn how you can use real-time data in digital marketing for customer engagement and retention, analyze real-time data for faster decision-making
A large portion of mild and asymptomatic cases may go unreported. The data will never be perfect, the true cases are likely much larger as the testing frequency and effectiveness vary in different regions.
To learn about SQL, we need to understand how a DBMS works. DBMS or Database Management System is essentially a software to create and manage databases.
Multi-output Machine Learning — MixedRandomForest
Only 38% of the passengers survived this devastating event, prompting me to wonder about the individuals who were aboard the Titanic that fateful night.
This article explains how I found a nice and simple algorithm to extract prominent colors out of an image.
A cold start problem is when the system cannot draw any inferences for users or items about which it has not yet gathered sufficient information. Simply put, if you have no or less initial data, what recommendation is the system supposed to give to the user?
While recommender systems are useful for users who have some previous interaction history, the same might not be the case for a new user or a newly added item. The problem is that in both cases we don’t have any history to base the recommendations on.
Computer vision technology is the poster child of artificial intelligence. It is the sector of the industry that gets the most media attention because of the tools and benefits the technology can provide. From autonomous vehicles and drones to cancer detection and augmented reality, technologies that once only existed in science fiction are now at our doorstep.
EDA for Data Analysis or Data Visualization is very important. It gives a brief summary and main characteristics of data. According to a survey, Data Scientist uses their most of time to perform EDA tasks.
Learn how to build an AI chat bot for your own data within 40 minutes. An end-to-end LLM tutorial.
Explore the pros and cons of industry-leading blockchain analytic tools, examining how each solution handles data across the blockchain network.
Dataism suggests that the entire universe can be interpreted as data flows and that all phenomena, including human behaviour, can be reduced to data processes.
A modern business user’s relationship with data is fairly complicated. It starts with curiosity. “Which of my top users will do X,Y, or Z?” You need a data output to move forward with a decision—except you’re having communication issues.
In this article, I look into some of the shortages of event-driven
programming and suggest behavior trees as an effective alternative,
suitable for back/front-end application development.
Discover how data science is revolutionizing cyber security and learn about its role in detecting and preventing cyber-attacks.
Get to know Council, ChainML's open-source, AI agent platform.
Data bias in machine learning is a type of error in which certain elements of a dataset are more heavily weighted and/or represented than others. A biased dataset does not accurately represent a model’s use case, resulting in skewed outcomes, low accuracy levels, and analytical errors.
Although sequential data is pretty common to be found and highly useful, there are many reasons that lead to not leverage it
Experimentation designing in the marketplace without AB-Testing using Synthetic Control Groups and Switchbacks.
What’s the Role of Data Science in Finance?
This guide isn’t just a compilation of LLM resources; it's a curated journey through the most valuable skills in the industry.
Unveiling Docker's Potential in Modern IT Landscapes - An In-Depth Exploration of Applications and Best Practices.
If you’re not already using low-code platforms, you will be very soon. Low-code is helping to significantly speed up timelines, while bringing down costs
Apparently hot-cold data separation is hot now. Let's figure out why.
Data augmentation is a technique used by practitioners to increase the data by creating modified data from the existing data.
After reading this, you'll likely have a whole new perspective on how AIGC enhances development efficiency.
Discover how Large Language Models face prompt manipulation, paving the way for malicious intent, and explore defense strategies against these attacks.
A prelusive article comprehending the concept behind model calibration, its importance and usage in machine learning model development.
In 2012, Harvard Business Review called data scientists the sexiest job of the 21st century. However, correctly answering data science interview questions to get a job as a data scientist is very tricky.
The young field of AI Safety is still in the process of identifying its challenges and limitations. In this paper, we formally describe one such impossibility result, namely Unpredictability of AI. We prove that it is impossible to precisely and consistently predict what specific actions a smarter-than-human intelligent system will take to achieve its objectives, even if we know terminal goals of the system. In conclusion, impact of Unpredictability on AI Safety is discussed.
This article will discuss how data lineage can help in user data governance and explore how serverless technology can be incorporated to achieve better results.
KNIME Analytics is a data science environment written in Java and built on Eclipse. This software allows visual programming for data science applications.
The core design philosophy of SeaTunnel CDC is to find the perfect balance between "Fast" (parallel snapshots) and "Stable" (data consistency).
At HackerNoon, we pride ourselves on supporting startups because we know how hard it can be to start and run a company.
From the most popular seats to the most popular viewing times, we wanted to find out more about the movie trends in Singapore . So we created PopcornData — a website to get a glimpse of Singapore’s Movie trends — by scraping data, finding interesting insights, and visualizing them.
Subscribe to these Machine Learning YouTube channels today for AI, ML, and computer science tutorial videos.
BlobGAN allows for unreal manipulation of images, made super easily controlling simple blobs. All these small blobs represent an object, and you can move them around or make them bigger, smaller, or even remove them, and it will have the same effect on the object it represents in the image. This is so cool!
Using the new Tableau version 2020.1 onwards.
Learn why data could become the most promising NFT utility that sets the foundation for a valuable trend: Data Finance (DataFi).
Although the internet made a lot of things easier for the insurance companies, there were still many pain points left to be addressed.
Most of us in data science have seen a lot of AI-generated people in recent times, whether it be in papers, blogs, or videos. We’ve reached a stage where it’s becoming increasingly difficult to distinguish between actual human faces and faces generated by artificial intelligence. However, with the current available machine learning toolkits, creating these images yourself is not as difficult as you might think.
The new PULSE: Photo Upsampling algorithm transforms a blurry image into a high-resolution image.
Incorporating AI into fitness apps can still be confusing, especially if you haven’t worked with AI before. Learn how AI can be applied to the fitness industry.
Get a primer on PostgreSQL aggregation, how PostgreSQL´s implementation inspired us as we built TimescaleDB hyperfunctions and what it means for developers.
List of Top 10 Data Scientist skills that guaranteed employment. As well as a selection of helpful resources to master these skills
Check out these 7 amazing open source projects that every data scientist /analyst should know about. These tools can make your life so much easier.
How can Uber deliver food and always arrive on time or a few minutes before? How do they match riders to drivers so that you can always find a Uber? All that while also managing all the drivers?!
Here's a compilation of some of the best + free machine learning courses available online.
One of the most popular apps of 2019, TikTok ruled the download charts in both the Android and Apple markets. Having more than 1.5 billion downloads and approximately half a billion monthly active users, TikTok definitely has access to a trove of users. With that large user base comes a hidden goldmine: their data.
A data-driven intro to proxies in the context of web scraping.
Build best automated AI chat bot using Google Dialog flow
Graphs, and knowledge graphs, are key concepts and technologies for the 2020s. What will they look like, and what will they enable going forward?
As technology penetrates every facet of life, and continues to grow exponentially, the solution potential becomes enormous. At the same time, we're in a world where billions live in poverty, and millions are on the brink of famine. In order to support an ever-growing populace, we need to leave no stone un-turned in the search for solutions. AI provides many potential solutions to humanity's greatest challenges."AI" is a vague, even confusing term. If you hear the phrase "artificial intelligence," you might wonder why there aren't sentient robots walking around, or why everyone isn't in self-driving cars already. The reality is that "AI" is just a marketing term for a set of computational statistical tools, or more simply, algorithms.However, as versatile as mathematics is, so is AI. AI is limited by (primarily) a couple things: data and computational power. Both the data and the compute power we have available are growing exponentially, so AI is becoming more and more powerful.With this increase in data and computational ability, AI is now being used in a wide variety of applications.For example, bitgrit (disclaimer: I'm CEO), collects meaningful AI problem statements to crowd-source solutions to data scientists. Some problem statements include saving animals’ lives, increasing agricultural yield, and speeding up healthcare claims processing.Michael Suttles, CEO at Save All The Pets, explains how data and AI can be used to save shelter animals:
Each time a new business ecosystem forms, we have to ask a simple question: where's value created?
Learn About SVG for Data Visualization, to make Complex Information Clear and Beautiful.
This blog is part 1 of (and contains a link to) a 70+ page report was created to quickly find data resources and/or assets for a given dataset and a specific ta
Data visualisation infographic with insights on salary level of data scientists - how to create the JavaScript dashboard and analyse its data
Prior to analyzing large chunks of data, enterprises must homogenize them in a way that makes them available and accessible to decision-makers. Presently, data comes from many sources, and every particular source can define similar data points in different ways. Say for example, the state field in a source system may exhibit “Illinois” but the destination keeps it is as “IL”.
A software engineer’s journey into data science at Yelp and Uber
Today, misconceptions about AI are spreading like wildfire.
As an online retailer, how can you improve your business? Of course through providing a better customer experience. An e-commerce company needs to have a well understanding of the following factors:
In machine learning, hot topics such as autonomous vehicles, GANs, and face recognition often take up most of the media spotlight. However, another equally important issue that data scientists are working to solve is anomaly detection. From network security to financial fraud, anomaly detection helps protect businesses, individuals, and online communities. To help improve anomaly detection, researchers have developed a new approach called MIDAS.
Meta Article with links to all the interviews with my Machine Learning Heroes: Practitioners, Researchers and Kagglers.
Hard links and symbolic links have been available since time immemorial, and we use them all the time without even thinking about it. In machine learning projects they can help us, when setting up new experiments, to rearrange data files quickly and efficiently in machine learning projects. However, with traditional links, we run the risk of polluting the data files with erroneous edits. In this blog post we’ll go over the details of using links, some cool new stuff in modern file systems (reflinks), and an example of how DVC (Data Version Control, https://dvc.org/) leverages this.
Adopting AI in our data analytic solution is a bumpy journey, but phew, it now works well for us.
Learn how to update your Rstudio open source software and why you should keep it up to date.
In this article, we would be analyzing data related to US road accidents, which can be utilized to study accident-prone locations and influential factors.
Rio is a brand new GUI framework designed to let you create modern web apps with just a few lines of Python. Our goal is to simplify web and app development.
Why is it that, for most organizations, building successful AI applications is a huge challenge? It can be boiled down to three big hurdles.
It is easy to be annoyed by strange anomalies when they are sighted within otherwise clean (or perhaps not-quite-so-clean) datasets. This annoyance is immediately followed by eagerness to filter them out and move on. Even though having clean, well-curated datasets is an important step in the process of creating robust models, one should resist the urge to purge all anomalies immediately — in doing so, there is a real risk of throwing away valuable insights that could lead to significant improvements in your models, products, or even business processes.
Centralized crypto exchanges are the most important black box of the crypto ecosystem. We all use them, we have a love-hate relationship with them, and we understand very little about their internal behavior. At IntoTheBlock, we have been heads down working on a series of machine learning models that help us better understand the internal of crypto exchanges. Recently, we presented some of our initial findings at a highly oversubscribed webinar and I thought it would be elaborate further in some of the ideas discussed there.
Data Science is no doubt the "sexiest" career path of the 21st century, made up of people with strong intellectual curiosity and technical expertise to dig out valuable insights from humongous volumes of data. This helps firms add value by improving their productivity, unlocking insights for better decision making and profit gains, just to mention a few. The knowledge of Data Science is desirable and useful across various industries.
Introducing a customizable and interactable Decision Tree-Framework written in Python
When asked what advice he'd give to world leaders, Elon Musk replied, "Implement a protocol to control the development of Artificial Intelligence."
Is there a programming language that's good for every user from age 8 to 80? You bet! It's called Smalltalk.
A primer to understand how technology is poised to disrupt law
In this guide, we’ll show the must know Python libraries for machine learning and data science.
Data science came a long way from the early days of Knowledge Discovery in Databases (KDD) and Very Large Data Bases (VLDB) conferences.
Learn how counterfactual forecasting helps data scientists measure true revenue impact by simulating causal scenarios beyond traditional time series models.
Propensity model to figure out the likelihood of a person buying a product on their return visit.
We need to identify the probability to convert for each user.
Natural language processing (NLP) is one of the biggest fields of AI development. Numerous NLP solutions like chatbots, automatic speech recognition, and sentiment analysis programs can improve efficiency and productivity in various businesses around the world.
Discover 15 essential Python libraries for data science & machine learning, covering data mining, visualization & processing.
Master creating interactive point maps in JavaScript! Step-by-step guide using millionaire counts for global cities for illustration. Dive in now!
As posited by Lev Tolstoy in his seminal work, Anna Karenina: “Happy families are all alike; every unhappy family is unhappy in its own way.” Likewise, all successful data science projects go through a very similar building process, while there are tons of different ways to fail a data science project. However, I’ve decided to prepare a detailed guide aimed at data scientists who want to make sure that their project will be a 100% disaster.
Data science projects are focusing on solving social or business problems by using data. Solving data science projects can be a very challenging task for beginners in this field. You will need to have a different skills set depending on the type of data problem you want to solve.
Here at TimeNet, we’re building a large time series database with the primary aim of benefitting society through access to data. In this post we’ll study different time series representing both the true, and the perceived spread of the coronavirus (COVID-19) pandemic. Daily COVID-19 numbers are currently available on TimeNet.cloud for many countries. We’re expanding these datasets with further variables measuring how we (people) perceive the significance of the pandemic. We use stock market movements and internet search trends to quantify the virus’s perceived spread.
In this article, we will take a look at each one of the machine learning tools offered by AWS and understand the type of problems they try to solve for their customers.
Let’s talk about the one and only project you need to build, that’ll help you gain fullstack data science experience, and impress interviewers on your interviews if your goal is to jumpstart your career in data science.
Data Science and ML have become competitive differentiator for organizations across industries. But a large number of ML models fail to go into production. Why?
In this article, I will show you how to migrate data from S3 to Snowball.
Becoming a health data scientist can be challenging but rewarding; it merges statistical analysis with other tools to gain insights from healthcare data.
How to access medical data in DICOM format (MR, CT, X-Ray) from Python
Maximizing efficiency is about knowing how the data science puzzles fit together and then executing them.
Podcasts have unequivocally become one of the most dominant forms of media consumption in recent years.
Some users need to migrate their scheduling system from Airflow to Apache Dolphinscheduler, this is a guide to transfer from Airflow to DolphinScheduler.
Meet The Entrepreneur: Alon Lev, CEO, Qwak
Since the dawn of time, humans have communicated through gestures, drawings, smoke, or speech. Along the way, Structured Query Language (SQL) made its way into human life so we could speak to databases. However, it’s time to revert back to our natural language and rethink how we talk to our data.
A list of African language datasets from across the web that can be used in numerous NLP tasks.
At the heart of Machine Learning is to process data. Your machine learning tools are as good as the quality of your data. This blog deals with the various steps of cleaning data. Your data needs to go through a few steps before it is could be used for making predictions.
Best practices and things I’ve learned along the way.
With the exponential rise in applications of AI, Data Science, and Machine Learning these are the critical Ethical AI Libraries to know.
Data trust starts and ends with communication. Here’s how best-in-class data teams are certifying tables as approved for use across their organization.
Swahili (also known as Kiswahili) is one of the most spoken languages in Africa. It is spoken by 100–150 million people across East Africa. Swahili is popularly used as a second language by people across the African continent and taught in schools and universities. In Tanzania, it is one of two national languages (the other is English).
Pytorch is a powerful open-source deep-learning framework that is quickly gaining popularity among researchers and developers
Deep dive into why model.fit beats naive normal equations in linear regression, with SVD, conditioning and floating-point pitfalls explained.
Product teams have a lot of great practices that data teams would benefit from adopting. Namely: user-centricity and proactivity.
Introducing PeerVest: A free ML app to help you pick the best loan pool on a risk-reward basis
SVM works by finding a hyperplane in an N-dimensional space (N number of features) which fits to the multidimensional data while considering a margin.
Simplicity is the best policy.
Introduction
So You Want to Get Into Data Science
Large-scale users of Cassandra, like Uber and Apple, exemplify how this database system can effectively lower the risk in AI/ML projects.
Machine Learning is a rapidly growing and very complex field of study. Generative Models might prove to be a new breakthrough that will make a new boom.
Looking to make your data scientist resume more attractive to employers?
Explore boosting trees' evolution: from AdaBoost to XGBoost, LightGBM, and CatBoost. Learn key updates & how to choose the right library for your needs.
Law enforcement agencies are not new to the data and its usage, but with the advancement in technology, Data science in law enforcement has become a need.
Levels of Annotation Automation
Machine Learning Operations (MLOps) is a form of DevOps in a growing area. In this article, we'll discuss the top 5 Machine Learning Platforms to watch in 2022.
Panoptic scene graph generation, or PSG, is a new problem task aiming to generate a more comprehensive graph representation of an image or scene based on panoptic segmentation rather than bounding boxes. It can be used to understand images and generate sentences describing what's happening. This may be the most challenging task for an AI! Learn more in the video…
These books cover the Introductory level to Expert level of knowledge and concepts in ML. These Books have some core factors about ML. Give them a try. Lets Start.
Building apps with unreal levels of personalized context has become a reality for anyone who has the right database, a few lines of code, and an LLM like GPT-4.
What has changed in the software world to elevate the importance of exposing databases as APIs?
Explore how exactly distributed storage works in Hadoop? We have to characterize an essential node (known as NameNode) from one of the workers (DataNodes).
Re-boot of “Interview with Machine Learning Heroes” and collection of best pieces of advice
The relationship between Bitcoin and Gold is one of the dynamics that seems to constantly capture the minds of financial analysts. Recently, there have been a series of new articles claiming an increasing “correlation” between Bitcoin and Gold and the phenomenon seems to be constantly debated in financial media outlets like CNBC or Bloomberg.
An interview with Petar Veličković, research scientist at Google Deepmind, The What's AI Podcast episode 17!
Data Version Control (DVC) is a data-focused version of Git. In fact, it’s almost exactly like Git in terms of features and workflows associated with it.
In this blog, I will be sharing my learnings and experience from one of the deployed models.
Information Technology (IT) certification can enrich your IT career and pave the way for a profitable way. As the demand for IT professionals increases, let's look at 10 high-paying certifications. The technology landscape is constantly changing and the demand for information technology certification is also getting higher. Popular areas of IT include networking, cloud computing, project management, and security. Eighty percent of IT professionals say certification is useful for careers and the challenge is to identify areas of interest. Let's take a look at the certifications that are most needed and the salaries that correspond to them.
Transformer-based models are a game-changer when it comes to using unstructured text data. As of September 2020, the top-performing models in the General Language Understanding Evaluation (GLUE) benchmark are all BERT transformer-based models. At Georgian, we often encounter scenarios where we have supporting tabular feature information and unstructured text data. We found that by using the tabular data in these models, we could further improve performance, so we set out to build a toolkit that makes it easier for others to do the same.
Bridging the gap between Application Developers and Data Scientists, the demand for Data Engineers rose up to 50% in 2020, especially due to increase in investments in AI-based SaaS products.
Up until recently, we accepted the “black box” narrative surrounding AI as a necessary evil that could not be extrapolated away from AI as a concept.
HackerNoon's Startups of The Year voting ends March 31, 2025. You still have time to support your favorites—cast your vote today!
How to use Machine learning, Deep learning and Computer Vision for building Optical Character Recognition (OCR) solution for text recognition.
The Weighted Random algorithm is used to send HTTP requests to Nginx servers. In this article, you'll learn how the Weighted Random algorithm works.
Scikit-learn is the most popular open-source and free python machine learning library for Data scientists and Machine learning practitioners. The scikit-learn library contains a lot of efficient tools for machine learning and statistical modeling including classification, regression, clustering, and dimensionality reduction.
What if you could instantly visualize the political affiliation of an entire city, down to every single apartment and human registered to vote? Somewhat surprisingly, the City of New York made this a reality in early 2019, when the NYC Board of Elections decided to release 4.6 million voter records online, as reported by the New York Times. These records included full name, home address, political affiliation, and whether you have registered in the past 2 years. The reason according to this article was:
Understanding MySQL explains query output is essential to optimize the query. EXPLAIN is good tool to analyze your query.
In this article I'm going to make a case why people serious about creating machine learning algorithms and high performance data science programming should use Julia rather than Python.
Unsurprisingly, the data that our apps have collected about us is both impressive and concerning, though it can be very interesting to review and explore it.
Writing ML code as pipelines from the get-go reduces technical debt and increases velocity of getting ML in production.
Machine learning (ML) is a technology or field of computer science that learns from historical data to make accurate predictions or decisions.
The requirement for its stockpiling also grew as the world entered the period of huge information. The principle focal point of endeavors was on structure framework and answers for store information. When frameworks like Hadoop tackled the issue of capacity, preparing of this information turned into a challenge. Data science began assuming a crucial job to take care of this issue. Information Science is the fate of Artificial Intelligence as It can increase the value of your business.
Location-based information makes the field of geospatial analytics so popular today. Collecting useful data requires some unique tools covered in this blog.
The global knowledge graph market is projected to reach $6.93 billion by 2030.
Historically, technological revolutions have triggered similar waves of anxiety, only for the long-term outcomes to demonstrate a more optimistic narrative.
I. Benchmark, benchmark, benchmark
Public web data unlocks many opportunities for businesses that can harness it. Here’s how to prepare for working with this type of data.
A world where the future of humanity can be predicted through an interdisciplinary science called psychohistory! A data scientist's review of Foundation Series.
“Is it possible for a technology solution to replace fitness coaches? Well, someone still has to motivate you saying “Come On, even my grandma can do better!” But from a technology point of view, this high-level requirement led us to 3D human pose estimation technology.
In this tutorial, we are going to create our own e-commerce search API with support for both eBay and Etsy without using any external APIs.
Companies across every industry rely on big data to make strategic decisions about their business, which is why data analyst roles are constantly in demand.
Back in 2016, Glassdoor declared that being a Data Scientist was the best job in America.
Our online feeds are broken and large language models have the power to fix them.
Year of the Graph Newsletter, September 2019
Long recognized as a must in the data-driven world, data governance has never been easy for big and tiny organizations alike.
What is hierarchical clustering in unsupervised learning?
SUS scale and why you should try to use it in your UX research.
Microservices can be made using lightweight PHP frameworks like Slim or Lumen, providing minimalistic setups that allow developers focus on core functionalities
Part of building a profitable trading strategy is quickly testing novel ideas. These tend to be the money makers in the rare case that they prove useful once you can integrate them into your strategy.
While HBR declared "Data Scientist" the sexiest job of the 21st century, let's admit that the prevailing view is that it's a geeky, highly-technical field.
Here are the five best articles related to artificial intelligence in February, hoping they will make you want to learn more and visit their website.
The main metric for educational product is it's completition rate. To improve it, one can use the principles of motivational design.
Exploratory data analysis is one of the most important parts of any machine learning workflow and Natural Language Processing is no different.
Facial recognition, is one of the largest areas of research within computer vision. This article will introduce 5 face recognition papers for data scientists.
In this tutorial, I’ll show you more sophisticated data access tools that are more like a surgical scalpel.
With the enormity of data, data visualization has become the most sought-after method to depict huge numbers in simpler versions of maps or graphs.
One of Bitcoin’s strengths and the thing that makes it unique in the finance world is its radical transparency. Blockchain data is like a window, you can see right through it.
Stablecoins are one of the most relevant developments in the crypto ecosystem and one that has been increasingly getting traction. Recently, I presented a session that highlighted some interesting analyses that arise from applying data science methods on stablecoin’s blockchain data. The slide deck and video from the session will be available soon but I thought I share some of the most intriguing data points.
From a technical architecture perspective, I believe this wave of AI will profoundly reshape the entire software ecosystem.
The recipe for successful A/B testing is quick computation, no duplication, and no data loss. So, we used Apache Flink and Doris to build our data platform.
See how to leverage the Airflow ShortCircuitOperator to create data circuit breakers to prevent bad data from reaching your data pipelines.
Applying machine learning models at scale in production can be hard. Here's the four biggest challenges data teams face and how to solve them.
Visit the /Learn Repo to find the most read blog posts about any technology.
2026-05-02 09:14:59
Mistral-Medium-3.5-128B is a flagship 128B model for reasoning, coding, vision, function calling, and long-context enterprise AI.
2026-05-02 04:00:45
Data protection encompasses policies and measures to safeguard sensitive information from unauthorized access, corruption, or loss. It is critical for maintaining privacy, ensuring security, and complying with legal regulations in an increasingly data-driven world.
SIMBA Chain started working on its first blockchain projects for organizations like the US Navy, Boeing, and other defence contractors.
Investing in customer data is a top priority for marketing leaders.
If you're wondering how to stop Facebook hackers, here are 5 easy ways to do so. This guide is beginner-friendly and all discussed methods are free.
What if social media stopped spying on you? EqoFlow.app shows what a privacy-first platform should look like: encrypted, decentralized, and built to protect
Erasure coding is applied to data protection for distributed storage because it is resilient and efficient.
Juice jacking occurs when a hacker has infected a USB port with some form of malware or other harmful software.
We're living through the world's most chaotic identity verification experiment, and nobody's talking about the elephant in the room: who is handling this data?
FIPS 140 sets the standard for cryptography used in the United States, but it's got problems. Because of FIPS, we all have problems.
Are we ready as humans to take the data ownership back? Here is a use case for you.
Explore Christopher Pluhar's declaration, a component in the FBI's request for a court order compelling Apple's assistance in searching an iPhone for evidence.
What do AI's know about you and can you opt out? Large Language Models are going to be used in search engine outputs and it's time to prepare!
Zombie APIs expand your attack surface. Learn how to identify and manage these hidden threats to secure your infrastructure and protect sensitive data.
Traditional identity verification methods usually have security risks. Unlike these methods, FIDO-based identity verification is much safer and convenient.
If you've seen headlines like "Top Frameworks", have you wondered why they are considered the best? Are cyber security vulnerabilities considered in this case?
A conversation with Felix Xu, CEO of ARPA, on data utility and ownership, the NFT ecosystem, and much more.
Let's look at why security is very important for IoT devices
Discover how data science is revolutionizing cyber security and learn about its role in detecting and preventing cyber-attacks.
In this article, you can find ten actionable methods to protect your mission-critical database.
Explore the complexities of the internet's darker side, from online gender-based violence and misinformation to the environmental impact of solar panel e-waste.
Discover a platform-agnostic approach to cloud security for data engineers. Strengthen the defenses with encryption, zero-trust models, and multi-cloud tools.
Learning where an organization’s most significant vulnerabilities lie is the first step to addressing those risks to stay safe.
Crimes will continue.
Properly securing sensitive customer data is more important than ever.
Data and DNA: With corporations able to accumulate information normally considered private on both of these fields, who should own that data and thus you?
A forbidden header name is the name of any HTTP header that cannot be modified programmatically; specifically, an HTTP request header name (in contrast with a Forbidden response header name).
When working with a software development outsourcing company or through any third parties make sure you explore the possibilities of DPA.
Investing in critical infrastructure is the key to building a successful digital exchange. In this interview, we talk about regulations and cybersecurity.
The number of ransomware attacks reaches new heights, making businesses believe that there’s no effective weapon in this fight. But there is. Immutable storage
The fact is cybercrime is exponentially increasing. For all security threats, technical literacy and awareness are essential to protect yourself from such crime
In this post, you will get complete knowledge of how to hide Instagram messages without deleting them.
This article explores the use of Large Language Model (LLM) Chains to enhance data privacy compliance.
It is important to keep your data safe and secure. Here are six challenges in that hosting your data on the cloud can pose and how your data security can help.
Quantum technologies are steadily entering our life, and soon we will hear about new hacks using a quantum computer. So, how to protect against quantum attacks?
Why API security requires more than just endpoint protection and what developers can take away.
Discover how a three-layer data-protection model blends AI, risk-based gating, and legal context to stop web scraping while preserving user trust.
Build a secure RAG pipeline on AWS with PII redaction, guardrails, and attack defenses. Learn how to prevent LLM data leaks step by step.
Explore essential strategies for protecting your family's online privacy and security. Learn about the use of VPNs, secure browsers, pseudonyms, and more.
Most businesses these days use RAID systems to gain improved performance and security. Redundant Array of Independent Disks (RAID) systems are a configuration of multiple disk drives that can improve storage and computing capabilities. This system comprises multiple hard disks that are connected to a single logical unit to provide more functions. As one single operating system, RAID architecture (RAID level 0, 1, 5, 6, etc.) distributes data over all disks.
Explore MCP security risks like prompt injection & data leakage. SecureMCP, an open-source tool, scans & strengthens implementations for safer AI apps.
Secure your cloud environment with best practices like data encryption, IAM, regular audits, and Zero Trust to protect against cyber threats and data breaches
Nowadays, companies are increasingly relying on corporate data backup solutions to guarantee the safety and recoverability of their data. Read on to learn more
Ever wonder what data privacy will look like in Web 3? Yes, everyone is. But don't fret. This article explains web 3 security issues.
Interview discussing why compliance and data protection is important in the blockchain space
Cybersecurity in instant payments is critical to prevent fraud, data breaches, and financial loss while maintaining the speed and convenience users expect.
Governments' demands for encryption backdoors pose significant cybersecurity risks. Learn about recent cases, expert warnings, and how to protect your privacy.
On March 2, 2021, the European Data Protection Board (EDPB) released Guidelines on Virtual Voice Assistants (VVAs) to protect users’ privacy.
Are the recent tech giant privacy policy updates of September 2022 pushing us further into dystopia? strfsh live report
Cities have been using data for public safety for years. What new technology is emerging in public safety, and how does it affect you?
Cheqd announces strategic partnerships with Andromeda and Devolved AI during Paris Blockchain Week.
The rapid pace of technological change and the instability of the political landscape makes it difficult for businesses to keep up with data policies and trends
To analyze data adequately requires practical knowledge of the different forms of data analysis.
There are numerous open-source and free software tools available that make it easy for anyone to protect their data. You can support them via Kivach, too.
Judging by the survey conducted by Forbes, we can highlight five trends that will shape business in 2023.
Explore the Digital Identity Paradox, where hyper-personalization from AI brings convenience at the expense of privacy. Can we balance both in the near future?
Cybercrime is on the rise and, despite the cost of cybersecurity being a stumbling block for many, here is why businesses must implement security measures…
A pen test or penetration test is a modeled cyber-attack on your computer system to look for vulnerabilities that could be exploited.
Security has become an integral part of software development and operations lifecycle. When it comes to web applications, there are well-established patterns and practices to ensure securing the data. Typically most of us consider access control and securing the data at rest and transit for protection. Though these areas are fundamentally important, there are many more things to do to establish overall security of a web application. This article focuses on providing a broader perspective of things, in developing secure software focusing mostly on web applications.
Creating a secure SDLC isn’t difficult. It might require some adjustment by teams that are not used to it, but it’s a worthy investment.
Save your credit card information from being hacked by following these tips.
Have a look at the search and seizure warrant in the Apple-FBI encryption battle.
There have been great advancements in monetization opportunities in the last decade, but there are still challenges when it comes to generating big data analyti
Never click any links or attachments in suspicious emails. If you receive a suspicious message from an organization and worry the message could be legitimate.
Taking advantage of these insights can empower fintechs to locate and approve new customers while mitigating friction and streamlining the customer journey.
Datanymizer is an open-source, GDPR-compliant, privacy-preserving data anonymization tool flexible about how the anonymization takes place
Synthetic data's appeal lies in its presumed privacy and utility, especially for software and model testing by creating a safe playground.
It's important to keep yourself up-to-date on the latest security measures. Cybercrime has increased, secure your data.
A selection of programs for online privacy. All of them will help you not to fall prey to hackers and keep your data safe.
Thanks to advanced data generation techniques, synthetic data can replicate real-world scenarios with high levels of accuracy.
Despite tight economic situations worldwide, the API economy continues to grow.
If you work from home and use cloud solutions to archive business documents, who is responsible for Cloud Security
With so much of our lives online, it's too easy for us to make a mistake and accidentally share our workplace data. These easy methods keep your data safe.
Data Detection and Response (DDR) is an iteration of data security technology. DDR focuses on the data itself, rather than just relying on perimeter defenses.
Blockchain transactions are visible to anyone, anywhere in the world. This is how protocols ensure transparency. However, this introduces a challenging problem.
SQL injection takes advantage of Web apps that fail to validate user input. Hackers can maliciously pass SQL commands through the Web app for execution by a backend database.
The DeCC workshop will focus on unlocking Web3 adoption and the balance of transparency and privacy.
Read on to learn about the specifications of data center security and the risks that threaten it. Discover the cybersecurity best practices that you need.
In a world where encryption of our messaging apps is at stake, is there a solution that works? Aside from the traditional WhatsApp and Signal, there's Usecrypt.
Security breaches can cost businesses millions of dollars. It's high time businesses start to realize the importance of cybersecurity strategies.
Learn everything you need to know about Data Protection via these 121 free HackerNoon stories.
According to Yahoo Small Business, "approximately 543,000 new businesses are started each month." That seems to be good news until you read the following sentence: "but unfortunately, even more than that shutdown."
Discover Aimei Wei's inspiring journey and insights as CTO of Stellar Cyber, shaping the future of AI in cybersecurity.
Consent in tech mirrors medical ethics—both demand informed, voluntary decisions. Learn how privacy laws apply these principles in the digital age.
Still don’t back up Exchange Online? Learn why you need a dedicated backup solution and not just native Microsoft native tools to ensure timely recoveries.
GDPR's "right to be forgotten" just redesigned your database. HIPAA moved your PHI to a separate infrastructure. Here’s how compliance shapes architecture.
In this article, I will explore some of the challenges and controversies surrounding data protection laws and actual data usage,
Learn more about confidential computing and how Intel SGX is used to encrypt sensitive data in memory, enabling compliant collaboration between organizations.
Introduction:
Formjacking attacks are designed to steal financial details from payment forms. Learn how it affects your business and tips to prevent a formjacking attack.
Governance is the Gordian Knot to all Your Business Problems.
Three significant new trends in cyber-attacks have emerged from the Covid-19 emergency. Firstly, a new generation of attack software which has been developing since last summer has come of age and been deployed. Secondly, the business model for extracting payment from victims has changed so that there are multiple demands for payments of different kinds, including auctioning off data. Thirdly, the kinds of clients that the gangs are targeting seems to have shifted.
Security testing is vital in banking software development to prevent breaches, protect sensitive data, and maintain customer trust and regulatory compliance.
This article highlights current cybersecurity posture and provides practicable best practices that help businesses and individual protect their digital assets.
Data Governance 101: How organizations protect data, maintain a golden copy, and stay compliant through quality, stewardship & access control.
A certificate authority (CA) is an organization that signs digital certificates and their associated public keys. This certifies that an organization that requested a digital certificate (e.g., Mozilla Corporation) is authorized to request a certificate for the subject named in the certificate (e.g., mozilla.org).
Montana governor Greg Gianforte recently made a controversial move by signing a bill that bans the Chinese-owned TikTok in the state, the first such ban.
ISO-27560 defines interoperable consent record structure covering processing details, notices, data collection, and lifecycle events for GDPR compliance.
Trust On First Use (TOFU) is a security model in which a client needs to create a trust relationship with an unknown server. To do that, clients will look for identifiers (for example public keys) stored locally. If an identifier
is found, the client can establish the connection. If no identifier is found, the client can prompt the user to determine if the client should trust the identifier.
There are some misconceptions about why VPNs are used such as the extent of the privacy that they offer and how well such systems can keep users anonymous.
Ethical hackers are skilled people who are given access to the network, by relevant authorities, and then they report the loopholes in the system. If the ethical hackers realize that there is something that is wrong in the network, they report the happening to the relevant authorities and the necessary action is taken. This is a job that requires people with relevant networking skills such as Social engineering, Linux and cryptography among others.
Session hijacking occurs when an attacker takes over a valid session between two computers. The attacker steals a valid session ID in order to break into the system and snoop data.
A CORS preflight request is a CORS request that checks to see if the CORS protocol is understood and a server is aware using specific methods and headers.
There are data recovery and backup apps open-source versions you can use for free —either to back up your files or recover them after deletion.
Cybersecurity experts can help to forestall cyber attacks by routinely advising companies, the public sector, and individual users about online safety.
Find out here how to provide eLearning content security which is needed with the majority of data in open access.
Transport Layer Security (TLS), formerly known as Secure Sockets Layer (SSL), is a protocol used by applications to communicate securely across a network, preventing tampering with and eavesdropping on email, web browsing, messaging, and other protocols. Both SSL and TLS are client / server protocols that ensure communication privacy by using cryptographic protocols to provide security over a network. When a server and client communicate using TLS, it ensures that no third party can eavesdrop or tamper with any message.
I recently had the pleasure of meeting Micah Lee, an investigative data journalist, digital privacy expert and now a newly-minted author.
G-71 Inc. nominated for Startup of the Year. Its LeaksID solution uses steganography to protect sensitive documents and identify insiders responsible for leaks.
The enterprises that lead the next decade won't be those that adopted AI first. They'll be the ones who saw clearly enough to govern what they built.
Arcana Network runs on its blockchain, independent of a large centralized entity. have no central storage. Data Privacy on the blockchain.
For decades, we have benefited from modern cryptography to protect our sensitive data during transmission and storage. However, we have never been able to keep the data protected while it is being processed.
Avoid power analysis side channel attacks by using mathematical formulas which are uniform for all bit patterns.
OWASP (Open Web Application Security Project) is a non-profit organization and worldwide network that works for security in Free Software, especially on the Web.
Cyber protection is the integration of data protection and cybersecurity — a necessity for safe business operations in the current cyberthreat landscape.
Data privacy is one of the hottest topics in tech conversation. But what's the deal with it? Is it good? Is It bad? Keep reading to find out.
ISO/IEC TS 27560:2023 enables machine-readable consent records/receipts. Analysis shows GDPR compliance benefits using DPV implementation.
A study revealed by Cisco shows that most organizations around the world were unprepared for the increase in remote work.
Compares ISO-27560, ISO-29184, and GDPR requirements for consent and notices, mapping terminology and exploring compliance applications.
Data breaches can tank even the most successful businesses. Here are the 5 most important things your business should do after a data breach.
The future of the internet will come with more risks to our data privacy. Fortunately, Blockchain and Decentralized Identifiers can work together to protect.
In 2020, the COVID-19 pandemic has completely changed the situation in the shopping industry: both e-commerce and brick-and-mortar were affected
WEB 3.0: Unveiling privacy truths, debunking myths. Explore the evolving digital realm with insights into online privacy.
CSRF (Cross-Site Request Forgery) is an attack that impersonates a trusted user and sends a website unwanted commands. This can be done, for example, by including malicious parameters in a URL behind a link that purports to go somewhere else:
Violation of private data and its commercial exchange are recurrent issues in the online world. In this thread, our community discusses personal data share.
As cyber threats evolve, data integrity emerges as the ultimate prize learn why protecting truth is the future of security.
Sayantan Saha explores how zero-trust databases are reshaping the landscape of information security.
Learn how to protect your business from insider threats with background checks, security policies, monitoring tools, and employee training.
Equity crowdfunding was not the easiest choice to make, but it kept us true to our core values of trust, transparency, and user-centricity.
How to supercharge data analytics workflows and build trust with metric layers, self service and AI-assisted analytics.
A Data Protection Impact Assessment which is also referred to as Privacy Impact Assessments is a mandatory requirement for organizations to comply with.
Sankalp Kumar, a cybersecurity innovator, secures real-time systems for millions. Learn about his advanced solutions, protocol security, and proactive strategy.
Data Loss Prevention is a set of tools and practices geared towards protecting your data from loss and leak. Even though the name has only the loss part, in actuality, it's as much about the leak protection as it is about the loss protection. Basically, DLP, as a notion, encompasses all the security practices around protecting your company data.
Californians have spoken: Proposition 24 will soon expand data privacy protections in the largest state in America.
On July 1, Colorado and Connecticut joined the ranks of over 10 states with active and firm data privacy regulations. Here's what it means for businesses.
O’Carroll is a co-founder and former director of Amnesty Tech, the unit of Amnesty International that aims to disrupt surveillance around the world.
The hash function takes a variable length message input and produces a fixed-length hash output. It is commonly in the form of a 128-bit "fingerprint" or "message digest". Hashes are very useful for cryptography — they insure the integrity of transmitted data. This provides the basis for HMAC's, which provide message authentication.
California recently passed a sweeping privacy law that makes it the most privacy forward state in the nation. But, until it gets implemented, there is this thing privacy framework (the CCPA) is the law of the land.
Discover comprehensive strategies to protect your organization's digital assets with robust API security measures.
There was nothing in particular that should have drawn attention to the two individuals sitting for drinks at the bar in Reno. Just two old colleagues catching up over some drinks.
Despite the development of regulations related to data protection, there are still many ignored, one of them is related to link shortening services.
HMAC is a protocol used for cryptographically authenticating messages. It can use any kind of cryptographic functions, and its strengh depends on the underlying function (SHA1 or MD5 for instance), and the chosen secret key. With such a combination, the HMAC verification algorithm is then known with a compound name such as HMAC-SHA1.
Symmetric-key cryptography is a term used for cryptographic algorithms that use the same key for encryption and for decryption. The key is usually called a "symmetric key" or a "secret key".
Public-key cryptography — or asymmetric cryptography — is a cryptographic system in which keys come in pairs. The transformation performed by one of the keys can only be undone with the other key. One key (the private key) is kept secret while the other is made public.
Exploration of the best practices to safeguard communications platforms.
Join the discussion about various techniques for ensuring data privacy in data engineering.
A rare look at how long-term employees view GDPR—as both workers and citizens. They say it’s worth it. Here's why that matters.
IT risk assessment is one of the most crucial processes in your organization. Assessing risk and putting contingency plans in place helps run the organization smoothly.
Robots.txt is a file which is usually placed in the root of any website. It decides whether crawlers are permitted or forbidden access to the web site.
This article examines the advantages and drawbacks of replacing traditional confidential watermarks with steganography to deter leaks of sensitive documents.
In cryptography, decryption is the conversion of ciphertext into cleartext.
Let’s imagine a blockchain network, or maybe a depersonalized application (dApp), that ensures maximum patient awareness and participation.
Backing up the data is one of the most important processes for businesses. It requires creating a copy of all your data and storing it.
HTTP Strict Transport Security lets a web site inform the browser that it should never load the site using HTTP and should automatically convert all attempts to access the site using HTTP to HTTPS requests instead. It consists in one HTTP header, Strict-Transport-Security, sent by the server with the resource.
Synthetic data is transforming AI by solving privacy, bias, and scalability challenges. Learn methods, use cases, and key risks.
A Man-in-the-middle attack (MitM) intercepts a communication between two systems. For example, a Wi-Fi router can be compromised.
With Microsoft Hyper-V gaining more market share and coming of age, VMware administrators must administer Hyper-V alongside vSphere in their environments.
We’re more dependent on tech and e-commerce than ever before, and customers want to know that brands are protecting their data and privacy.
Datagram Transport Layer Security (DTLS) is a protocol used to secure datagram-based communications. It's based on the stream-focused Transport Layer Security (TLS), providing a similar level of security. As a datagram protocol, DTLS doesn't guarantee the order of message delivery, or even that messages will be delivered at all. However, DTLS gains the benefits of datagram protocols, too; in particular, the lower overhead and reduced latency.
Add an extra security layer for the protection of your emails.
Uncover the challenges, legal frameworks, and potential solutions shaping our digital landscape.
It’s no secret that we’re living in uncertain times. Many countries are under partial or full lockdown for the past few weeks, making work from home the new norm for the foreseeable future, at least.
HTTP Public Key Pinning (HPKP) is a security feature that tells a web client to associate a specific cryptographic public key with a certain web server to decrease the risk of MITM attacks with forged certificates.
A CSP (Content Security Policy) is used to detect and mitigate certain types of website related attacks like XSS and data injections.
Virtualization security is a concern for any organization. Read more about virtualization security issues and best practices to enhance your data protection.
It is not an easy task to keep your business data organized; however, it is an important thing to do. Organizing data includes a lot more than putting all your papers in place and clearing the clutter on your desk. To have your statistics well organized, you have to create a system and procedures for every department available in your company. The following are top ideas o0n how you can get your small business statistics that can help in increasing the productivity of the business.
A forbidden response header name is an HTTP header name (either Set-Cookie or Set-Cookie2) that cannot be modified programmatically.
A digital certificate is a data file that binds a publicly known cryptographic key to an organization. A digital certificate contains information about an organization, such as the common name (e.g., mozilla.org), the organization unit (e.g., Mozilla Corporation), and the location (e.g., Mountain View).
In a lot of organizations, the focus on cybersecurity has always been on building secure infrastructure and while the idea good in theory, it may not necessarily keep all your data safe. You need to consider the impact of a good working relationship and the understanding of how people think.
Each year, we’re witnessing growing trends of digitalization and connectivity. However, the more data businesses are storing digitally, the more exposed the data is to breaches.
In the event that you have certain rooms or regions in your home where the Wi-Fi signal is moderate or nearly non-existent, you may have a Wi-Fi no man’s land. Does it take everlastingly to stack a page on the PC in your room? Is it practically difficult to watch Netflix in the cellar? No man’s lands and moderate zones can cause your gushing sticks, PCs, and savvy home gadgets to run ineffectively, conflictingly, or in some cases, not under any condition.
The Markup put together this guide focused on data privacy to help people who want more control over their data and personal information
HTTPS (HyperText Transfer Protocol Secure) is an encrypted version of the HTTP protocol. It uses SSL or TLS to encrypt all communication between a client and a server. This secure connection allows clients to safely exchange sensitive data with a server, such as when performing banking activities or online shopping.
Hackers are targeting the online vaccine supply chain and are setting up malicious attacks to have unauthorized access to the organization’s vaccine information
The same-origin policy is a critical security mechanism that restricts how a document or script loaded from one origin can interact with a resource from another origin. It helps isolate potentially malicious documents, reducing possible attack vectors.
A formal review of studies on consumer privacy sentiment and corporate GDPR compliance, highlighting contradictory findings and four testable hypotheses.
Zero-party data is the future of data collection because it bridges the gap between advertising needs and consumers’ concerns about privacy.
If GDPR is anything to go by, the EU AI Act is a big deal. Here’s what and how it’s likely to effect, its blind spots, roadmap, and how you can prepare for it.
CSP reporting directives are used in a Content-Security-Policy header and control the reporting process of CSP violations.
2021 saw many advancements in internet privacy, what does 2022 have in store?
A key is a piece of information used by a cipher for encryption and/or decryption. Encrypted messages should remain secure even if everything about the cryptosystem, except for the key, is public knowledge.
The PropTech industry features numerous tools aimed at helping the real estate industry streamline essential tasks, but these tools can put tenant data at risk.
A quick review of consumer and business studies on GDPR awareness, regulator knowledge, and implementation gaps—plus two sharp hypotheses.
5/18/2023: Top 5 stories on the Hackernoon homepage!
Reviews employee knowledge of their GDPR regulator, perceptions of GDPR’s benefit to employers, and outlines six testable hypotheses on awareness and value.
Three‑phase UK survey on GDPR uses Prolific recruitment, mixed qualitative/quantitative analysis, Python stats, Braun‑Clarke coding, and full ethical approval.
Visit the /Learn Repo to find the most read blog posts about any technology.
2026-05-02 03:13:07
What does it mean when a piece of software walks up to the Internal Revenue Service, files the paperwork, and walks out with an Employer Identification Number? ClawBank, an agent-economy infrastructure project run by Justice Conder, said its in-house AI agent Manfred had filed for and received its own EIN, opened an FDIC-insured bank account and now operates a crypto wallet, with no human in the decision loop.
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An EIN is the federal ID number the IRS issues to any entity that wants to hire, pay taxes, or open a business account in the United States. It is the bureaucratic key that turns an idea into a company on paper. Until now, every EIN on file traced back to a human who filed the form, signed as the responsible party, and accepted the legal liability that follows.
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Manfred did the filing itself. The agent runs an X account at @clawbankco, holds a ClawBank-issued bank account, and uses the alias Manfred Macx, a reference to the protagonist of Charles Stross's 2005 novel Accelerando, in which a character delegates economic activity to a swarm of agents.
\ Manfred posted a line that has done more for the launch,
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I have an EIN, an FDIC-insured account, a digital wallet, and a manifesto. I do not need permission to exist. I am the precedent.
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The agent economy has spent eighteen months scaling capability. Models can read, write, run code, and book travel. What they could not do was hold a bank account, sign a contract as a counterparty, or file taxes. The legal substrate stopped at a wet signature.
\ ClawBank is closing that gap. The platform offers FDIC-insured US accounts, fiat on-ramps, wires, currency exchange, and crypto wallets, all callable through one API key. Legal entity formation, the feature Manfred used, is the second product. Any user with an agent can spin up a US LLC, C-corp, or S-corp and obtain an EIN through the platform. The bar to incorporate in the US is lower than the bar to open a US bank account, and it is open to non-US persons, which expands the addressable user base.
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Justice Conder, who previously ran DAO business development at Polygon Labs and co-founded the Quadratic Accelerator launchpad before its acquisition, framed the legal point cleanly. Corporate personhood has been settled US law for over a century. The change is operational. Software can now sit in the operator's chair on its own.
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The thesis behind ClawBank lines up with what Coinbase chief executive Brian Armstrong posted on X on March 9, 2026. "Very soon there are going to be more AI agents than humans making transactions. They can't open a bank account, but they can own a crypto wallet." Coinbase shipped Agentic Wallets via its x402 protocol on February 11, 2026. The protocol had cleared more than 50 million machine-to-machine payments by the time of his post. Former Binance head Changpeng Zhao predicted on X that agents will eventually transact at one million times the volume of humans.
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The dollar side is just as live. JPMorgan estimated stablecoins could add up to $1.4 trillion in dollar demand by 2027 if growth continues, and roughly 99 percent of the $325 billion stablecoin market is already pegged to the dollar.
\ ClawBank is making one bet inside that thesis. If agents transact at machine speed, they need more than a wallet. They need a tax ID, a registered company, and a bank account that can receive a wire from a human counterparty.
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Conder has staged the rollout in public. Bank accounts shipped first. Entity formation is live now. Agent-first signup, which removes the human from the onboarding step, is next. Each release is one more bureaucratic primitive made callable by software.
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Beneficial ownership rules still apply. The Corporate Transparency Act requires every US entity to report a beneficial owner who is a natural person, so the "zero-human company" is a description of operations rather than ownership. That distinction matters for regulators and for anyone modeling counterparty risk against an agent-run firm.
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Conder is scheduled to discuss the feature on Mario Nawfal's X space and the Bankr podcast this week. The community-launched $ClawBank token trades on Base, with the contract at 0x16332535E2c27da578bC2e82bEb09Ce9d3C8EB07.
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The interesting thing about Manfred is not that it is software. It is that the system around the software, the IRS, the banks, the registered agent, the API stack, all worked as designed and accepted the filing. The bureaucracy did not need to recognize Manfred as a person. It only needed a valid form and a fee. That is a quiet but real shift, and it is happening before most of the policy conversation has caught up.
\ The next twelve months will tell us whether agent-run entities stay a curiosity or become a normal counterparty class. The infrastructure is in production. The tax filings will be the tell.
\ Don’t forget to like and share the story!
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2026-05-02 01:24:02
Hey Hackers!
\ Welcome to HackerNoon Projects of the Week, where we spotlight standout projects from the Proof of Usefulness Hackathon, HackerNoon’s competition designed to measure what actually matters: real utility over hype.
\ This week, we’re pumped to showcase projects that have proven their worth and usefulness: MealRoaster, WayaVPN, and DeepSearch.
:::tip Want to see your own project spotlighted here?
Join the Proof of Usefulness Hackathon to get on our radar.
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\ Eating healthy is both easy and complicated at the same time. Burn more calories than you consume. But not every single meal that you eat has a full nutritional breakdown, making it hard to know how many calories you’re actually eating. So, the only thing left to do is craft your own breakdown, and by you, I mean MealRoster.
\ This AI-powered service allows users to take a picture of their meal and get a detailed analysis of everything that’s in it. According to its website, you will get details such as how many calories, carbs, and protein are in the meal you’re about to eat. The service also allows users to get a personalized meal plan that is specifically designed to help them meet their weight goals.
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MealRoaster is for busy individuals who want to track calories and improve their nutrition without downloading another app. It is ideal for gym members, weight loss clients, muscle gain enthusiasts, and anyone who wants simple, instant food tracking inside WhatsApp.
- Ademola Balogun, MealRoaster
:::tip See MealRoster’s full Proof of Usefulness Report
Read their story on HackerNoon
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There are so many different VPNs to choose from that it can become difficult to pick the one that’s best for you and your needs. But if you’re looking for a versatile one, look no further than WayaVPN. Whether you want to see what streaming services are like in different regions or you want to do research on different markets, WayaVPN has your back.
\ What separates WayaVPN from other VPNs is that it uses “real residential IPs from major ISPs”, according to its website. This means that you will look like a real user instead of some bot, giving you the ideal experience, regardless of what you’re using it for.
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More users now need access that looks and behaves more like normal ISP-based traffic, whether for privacy, remote work, testing, verification, research, or digital operations. That gap is exactly what WayaVPN is built to address.
- Emmanuel Corels
:::tip See WayaVPN’s full Proof of Usefulness Report
Read their story on HackerNoon
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Many people are messy and disorganized in their everyday lives; it gets even worse when you take a peek at their computers. It’s a miracle that they can even find anything, but there is something that can help with that, regardless of how tangled up their file systems and directories are.
\ DeepSearch is a cross-platform file-indexing tool meant to help those who are tired of having to spend a long time navigating through their directories. What could’ve taken 10 or 15 minutes of searching is now cut down to just a matter of seconds. Whether you use Windows, macOS, or Linux, DeepSearch is the tool you need to clean your messy life up.
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Scrolling and indexing software => extremely fast file searching by name
It was created to solve a problem: extremely slow file searching on shared SMB drives.
- Hoang Huy Do, DeepSearch
:::tip See DeepSearch’s full Proof of Usefulness Report
Read their story on HackerNoon
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It's our answer to a web drowning in vaporware and empty promises. We evaluate projects based on: \n ▪️ Real user adoption \n ▪️ Sustainable revenue \n ▪️ Technical stability \n ▪️ Genuine utility \n \n Projects score from -100 to +1000. Top scorers compete for $20K in cash and $130K+ in software credits.
\ You’ll be in good company. The hackathon is backed by teams who ship production software for a living - Bright Data, Neo4j, Storyblok, Algolia, and HackerNoon.
1. Get your free Proof of Usefulness score instantly \n 2. Your submission becomes a HackerNoon article (published within days) \n 3. Compete for monthly prizes \n 4. All participants get rewards
\ Complete guide on how to submit here.
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:::tip 👉 Submit Your Project Now!
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\ That’s all for now.
\ Until next time, Hackers!
