100+ Handpicked AI And Machine Learning Blogs & Communities

100+ Best Machine Learning and Artificial Intelligence Blogs to Follow in 2021

Hi Everyone, Hope you all are fine and safe in this pandemic. Today, In this post, We're gonna share a handpicked list of 100+ active, regularly updated and some of the best Artificial Intelligence, Machine Learning and Deep Learning blogs & communities. Let's dive in the various collection of some of the best machine learning blogs, computer vision blogs, artificial intelligence blogs, deep learning blogs, medium machine learning, kaggle, reddit machine learning and other deep learning community.

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Learn from experts (like Andrej Kaparthy, Sebastian Raschka, Jason Brownlee, Chip Huyen, etc), see how the giants like (Google, Uber, Spotify, OpenAI, Quora, NVIDIA, IBM, Twitter, etc) uses artificial intelligence, machine learning, deep learning & other emerging tech to build as well as to solve real world problems, and share your opinions, research papers & work with communities like (r/MachineLearning, r/LearnMachineLearning, etc), by following blogs & communities as per your requirement from the below given list.

100+ Handpicked Artificial Intelligence, Machine Learning and Deep Learning Blogs & Communities are

πŸ‘‰ Sebastian Ruder

Sebastian is a research scientist in the language team at DeepMind. At Ruder.io, the author shares articles about natural language processing, machine learning, and deep learning. A glimpse to some of his articles include "Recent Advances in Language Model Fine-tuning", "ML and NLP Research Highlights of 2020", "An Overview of Multi-Task Learning in Deep Neural Networks" and more.

A Must follow blog for machine learning and deep learning enthusiast. You should follow this blog because the articles are written by a senior director of Artificial Intelligence at Tesla. Andrej Karpathy is also a founding member of one of the best non profit AI company named OpenAI. Some of the recent stories on this blog are "Short Story on AI: Forward Pass", "A Recipe for Training Neural Networks", "What I learned from competing against a ConvNet on ImageNet" and more.

Peter Warden is an engineer, author of The Public Data Handbook and The Big Data Glossary for O’Reilly, builder of OpenHeatMap and the Data Science Toolkit and other open-source projects.

His blog has well-structured short articles that are informative and educational but they are not for beginners. The ML blog has no subsections, it has articles in the form of a directory that might escape out of the reach of those that are starting to learn about Machine Learning and Data Science.

πŸ‘‰ Sebastian Raschka 

Another must follow machine learning and deep learning blog, created by Assistant Professor of Statistics at the University of Wisconsin-Madison. It's different than normal blog. You will find personal opinion, tips, reviews, resources and more on his blog. Some of his latest stories are "Datasets for Machine Learning and Deep Learning -- Some of the Best Places to Explore", "Book Review: Deep Learning With PyTorch -- A Practical Deep Learning Guide With a Computer Vision Focus and an Interesting Structure", "How I Keep My Projects Organized" and more.

πŸ‘‰ Lilian Weng

A Machine Learning Blog by Lilian Weng, an applied AI research manager at OpenAI. Lilian covers various topics like Reinforcement Learning, Natural Language Processing, AutoML, Object Detection, Auto Encoder, Transformers, Meta Learning, and other topics. A glimpse to some of her latest stories include "How to Build an Open-Domain Question Answering System?", "Are Deep Neural Networks Dramatically Overfitted?", "Curriculum for Reinforcement Learning" and more.

πŸ‘‰ Sanyam Bhutani

A Blog from 2x Kaggle Grandmaster and Machine Learning Engineer at H2O.ai. A website full of  machine learning interviews with world's best experts like Jeremy Howard, Sebastian Ruder, Ian Goodfellow, Andrew Trask, Francois Chollet and other Kaggle Kernels. Apart from this, you will also find articles like “Sequence to Sequence Learning with Neural Networks”: Paper Discussion, "Introduction to Image Augmentations using the fastai library", “An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models” and more.

GoogleAI blog is a very good source for those who have an ongoing career in Artificial Intelligence and want to stay up to date with the latest advances.

On it, they publish articles about the latest news on the field, in a paper-like manner, which makes it hard to approach for people without a thorough understanding of Artificial Intelligence and Machine Learning. However, for those with some degree of expertise, this ML blog is gold.

πŸ‘‰  Jay Alammar

Jay Alammar, Machine Learning Engineer at Arpeggio and Deep Learning content creator at Udacity, visualize and explain machine learning concepts to thousands of learners via his blog articles and Udacity's Machine Learning, Deep Learning and Natural Language Processing Nanodegrees. Fetching latest stories from his blog includes "Finding the Words to Say: Hidden State Visualizations for Language Models", "Interfaces for Explaining Transformer Language Models" and more. 

πŸ‘‰ DeepMind Blog

DeepMind works on some of the most complex and exciting challenges in AI. Their world-class research has resulted in hundreds of peer-reviewed papers, including in Nature and Science. Join DeepMind and learn about their research works like "Traffic prediction with advanced Graph Neural Networks", "Dopamine and temporal difference learning: A fruitful relationship between neuroscience and AI". Also listen to some of their amazing podcast like Towards the Future, AI for Everyone, and more.

Professional developer and machine learning practitioner Jason Brownlee started this blog years ago as a resource to help other developers become well-versed in ML. Today, it remains a top-referenced blog for industry professionals looking to broaden their knowledge of ML concepts. Brownlee’s blog is updated frequently and is a treasure chest of educational information on AI.

With more than eleven years under its belt and 1.8M followers, r/MachineLearning subreddit is considered as the most popular machine learning communities. Followed by thousands of experts and researchers like Jeremy Howard, Hardmaru, Andrew Ng, Francois Chollet, etc, this subreddit is a powerhouse for those who wants to keep themselves updated with what's latest happening in this field. At Reddit ML, You can find many different threads with interesting information including resources – websites, blogs, detailed discussion on topics, research papers, projects, problems people face, and smart solutions to common difficulties.

πŸ‘‰ PyImageSearch

PyImageSearch is a website created by Adrian Rosebrock, PhD, professional Computer Vision/Deep Learning developer and researcher. He started the this blog to help other students, developers, and researchers become better at computer vision. He shows other people how to master Computer Vision and Deep Learning in a practical way instead of diving into theoretical stuff

πŸ‘‰ Import AI

The founder of Import AI is Jack Clark, A strategy and communication director at OpenAI. He offers in depth articles about Data, Machine Learning and Artificial Intelligence. This blog is not for beginners. Jack covers stories like "We can use reinforcement learning to get robots to walk now", "Why does measurement in AI matter? A talk by Jack Clark", "Using AI to improve game design" and more.

πŸ‘‰ The Spectator

Shakir Mohamed, a research scientist at DeepMind, writes about machine learning and deep learning on his blog. Shakir’s aim is to dive into computational science, machine learning, and statistics, as a single field. Therefore shows the interdisciplinary nature of the field of machine learning research while exploring its diverse themes and topics. 

πŸ‘‰ inFERENCe

A blog about machine learning research, deep learning, causal inference, variational learning, by Ferenc Huszar, a senior lecturer in machine learning at university of Cambridge.

πŸ‘‰ FloydHub's Blog

The regularly updated, reliably informative blog at this deep learning platform and Y Combinator alum has solidified itself as a trusted resource over the last three years. Penned by the company’s own data scientists and a roster of knowledgeable outside contributors (from organizations such as Microsoft Research, Intercom and Cognizant), posts are visualization-dense, code-snippet-packed deep dives on DL and ML concepts and approaches. 

πŸ‘‰ The BAIR Blog

The artificial intelligence research department at UC Berkeley created this blog to share research findings and important information about their AI-related work. Covering a spectrum of research-from natural language processing to robotics-grad students and faculty contribute content for both experts and the general population to consume.

πŸ‘‰ Colah's Blog

Christopher Olah portrays himself as a wandering machine learning researcher, looking to understand things clearly and explain them well. Olah is a researcher with Open AI and formerly at Google AI. His blog has complete and exciting articles for the machine learning researcher and enthusiast — a gold mine of free, open, machine learning research.

The Software Engineers, Developers, Machine Learning Engineers and other professionals working at Quora shares everything about the backend and frontend of Quora. You will find amazing articles like Applications of NLP at Quora, A Machine Learning Approach for Ranking answers on Quora, Web Server Architecture at Quora, MySQL sharding and adoption of Kubernetes ate Quora and more

This is also one of the best source for learning machine learning. This is not basically a publication or blog, its a tag page where medium curates all the stories that are related to machine learning. On this page, Medium scraps and shows some of the best as well as latest stories in machine learning.

Apple’s advancements in voice recognition, predictive text, and autocorrect leveraged for Siri signal some of its machine learning work. Apple Machine Learning Blog will help you to understand how ML shapes their different technologies, and Apple engineers give perspective on how their work influences the transformation of ML.

πŸ‘‰ Distill

Distill is technically not a blog--it’s an online research journal dedicated to machine learning and other topics. However, the scientific journal’s content and fresh presentation style warrant it a mention on this list. The website aims to present AI research in a more user-friendly way, incorporating reactive diagrams and compelling graphics that help the reader to more easily understand the research.

πŸ‘‰ DataMuni

A web community started by world's first 4x Kaggle Grandmaster named Abhishek Thakur, whose aim is to share no non-sense, to-the-point, peer-reviewed articles and tutorials about Machine Learning, Deep Learning, Artificial Intelligence, Python and Data Science.

At NVIDIA's Official Blog as well as on Developer's Blog, you will find news, podcasts and stories like What Will NVIDIA CEO Jensen Huang Cook Up This Time at NVIDIA GTC?, What Is Conversational AI?, NVIDIA’s Shalini De Mello Talks About Self-Supervised AI, NeurIPS Successes, German Researchers Develop Early Warning AI for Self-Driving Systems and more. 

Papers With Code highlights trending Machine Learning research and the code to implement it. The mission of PWC is to create a free and open resource with Machine Learning papers, code and evaluation tables.

This is the second most popular subreddit dedicated to machine learning. Redditors add valuable post like Math You Need to Succeed In ML Interviews, ask questions like What should my learning path be for Computer Vision and Deep Learning, How much data would I need for a computer vision model that can recognize people wearing sunglasses from security camera footage?, shares their project like Playing the 8 Queen Puzzle Game using PyGAD (Genetic Algorithm) and more.

πŸ‘‰ Kaggle Blog

At Kaggle Medium Blog, You will find interviews from Kaggle competitors and grandmasters like "First-time Competitor to Kaggle Grandmaster Within a Year | A Winner’s Interview with Sanghoon Kim", different guides like " I trained a model. What is next?" and more! 

IBM Artificial Intelligence needs no introduction. They have a commendable team of professionals who have worked in multiple industries over the years. In their artificial intelligence and machine learning blog, you will find solutions to issues that you might have faced as an engineer while coding and be sure to have a reliable community to talk to.

Uber Engineering is all about building scalable systems to move people and things to the physical places they need to go. Follow to keep up with machine learning articles from Uber Engineering.

πŸ‘‰ OpenAI Blog

OpenAI comes from industry leaders who want to bring AI to the masses. It is linked to the non-profit research company OpenAI, co-chaired by Elon Musk and Sam Altman, and sponsored by companies such as Amazon Web Services, Microsoft, and Infosys who are trying to make advanced AI more accessible to everyone. Contributors discuss their collective efforts to improve and advance AI technologies through long-term research. It’s a valuable resource for anyone interested in the future of AI.

πŸ‘‰ Tensorflow Blog

The official blog of Google’s powerful machine-learning library is regularly updated with digestible how to’s, creative use-case spotlights and introductions to new open-source packages. Whimsical case-study spotlights should engage general-interest readers, while rollout explainers-like the series focused on the low-lift TensorFlow Recommender package-will appeal to working data scientists and machine-learning engineers.

Connect with world's best organization and experts in artificial intelligence and machine learning via this list and keep yourself updated with latest happenings in the field of artificial intelligence and machine learning.

πŸ‘‰ Pytorch Blog

Speaking of Facebook Research, perhaps the most notable tool to emerge from FB R&D - the deep-learning framework PyTorch - sports a host of relevant content on its dedicated blog. There are plenty of interesting case studies (from Datarock to Disney), and a plethora of resources and community support for building and productionizing neural networks.

This blog will take you inside twitter. You will learn about, how twitter uses machine learning and artificial intelligence to solve various problems. If you're curious, here are some of their latest covers which includes "How we fortified Twitter's real time ad spend architecture", "Graph ML at Twitter", "Harnessing second order optimizers from deep learning frameworks" and more.

A must read machine learning blog. They drop articles like "Best Practices for Regression-free Machine Learning Model Migrations", "Building Flexible Ensemble ML Models with a Computational Graph", "Building a Gigascale ML Feature Store with Redis, Binary Serialization, String Hashing, and Compression" and more.

Amazon is massively involved in ML, using algorithms in nearly all areas of its business to create leads. The blog highlights projects and guides that reveal industry strides to readers and covers ML uses in Amazon Web Services technology.

Brighterion offers articles, news and thought leadership on artificial intelligence and machine learning. On their blog they covers articles like "The importance and challenges of ethical AI", "Building trust in AI throughout the digital user journey and credit risk lifecycle" and more.

StackOverFlow is not only for developers. If you're facing any problem or not, SOF ML will be still helpful for you. You will find experts answers to general as well as advanced questions about machine learning (concepts, theory, methodology, terminology etc). Some of the conceptual questions answered on StackOverFlow ML are "What is the role of the bias in neural networks?", "What is the difference between a generative and a discriminative algorithm?", "Loss & accuracy - Are these reasonable learning curves?" and more 

Led by a group of students at UC Berkeley, this blog is dedicated to building and fostering a vibrant machine learning community on campus while contributing to the greater machine learning community and beyond. Join ML at Berkeley and learn from articles like "A Survey of Applications of ML in Healthcare", "Neural Module Networks for Visual Question Answering", "What is Behavior al Cloning and How to use it?" and more. 

πŸ‘‰ Nuit Blanche

Nuit Blanche is a blog that focuses on Compressive Sensing, Advanced Matrix Factorization Techniques, Machine Learning as well as many other engaging ideas and techniques needed to handle and make sense of very high dimensional data also known as Big Data.

Towards Data Science is one of the largest Medium publications, dedicated to unveiling Data Science, Artificial Intelligence, and Machine Learning knowledge. In it, you can find all kinds of articles: from simple 101 Tutorials about Models, algorithms, and concepts, to explanations of scientific papers or complete end-to-end projects. It is a machine learning blog for beginners and experts alike, as there is such a large amount of content and a wide variety of articles that anyone can learn something.

πŸ‘‰ KDNuggets

KDNuggets is one of the most well-known Machine Learning and Data Science blogs out there. It is continuously posting articles about all sorts of topics related to these fields: from an easy hands-on explanation of algorithms to complex projects or advice. It contains a section with where to find many datasets, and a section about Artificial Intelligence-related jobs and PhDs, so be sure to take a look!

πŸ‘‰ Towards AI

Towards AI is an online medium publication, which focuses on sharing high-quality news, articles, and stories on Artificial Intelligence, Machine Learning, Deep Learning and technology related topics.

πŸ‘‰ ArXiv ML

ArXiv.org is one of the and top-voted great place to read research papers on a wide variety of topics like machine learning, data science deep learning, artificial intelligence, and more. The collection of research papers on the platform are over 1.5 million, with over40 ,000 papers for machine learning alone. It is a great place for those looking to get started on reading about ML and DL. The platform will also expose individuals to a wide range of applications of AI technology due to its vast range of well-written papers.

πŸ‘‰ Awesome Machine Learning Github Repos 

Dedicated communities of ML enthusiasts have created multiple lists of the must-reads in the machine learning and deep learning fields. These include not only curated lists of some of the influential papers published over the past few years, but also some hidden gems and a vast amount of knowledge. Some examples include Terryum‘s “Awesome – Most Cited Deep Learning Papers”, Floodsung‘s “Deep Learning Papers Reading Roadmap” collections and Joseph Misiti's Awesome Machine LearningA curated list of awesome machine learning blogs, professional machine learning events, frameworks, libraries, Softwares and more.

Pinterest Labs tackles the most challenging problems in Machine Learning and Artificial Intelligence. And through their engineering blog they share the solutions as well as different articles like how machine learning is implemented in Pinterest, Multi-task Learning for Related Products Recommendations at Pinterest, HierTCN: Deep learning models for dynamic recommendations and inferring user interests, Building A scalable data management system for computer vision tasks, and more. 

Netflix’s surfeit of user data has allowed for analytics-driven decisions both small (algorithmically personalized thumbnail art) and large (whether or not a production or title buy is greenlighted). It also means that, whenever Netflix reveals something about the inner workings of its data team, it’s usually worth a look. Recent technical highlights includes "Supporting content decision makers with machine learning", "Machine Learning for a Better Developer Experience", "Using Machine Learning to Improve Streaming Quality at Netflix" and more.

The Machine Learning Theory aka Hunch blog is an experiment by machine learning researcher John Langford. He has emphasized that the field of machine learning “is shifting from an academic discipline to an industrial tool”.

πŸ‘‰ Mark Tech Post

MarkTechPost blog has a dedicated section on free resources for Artificial Intelligence, Machine Learning, and other programming arenas along with tutorials. Interviews of known contributors to the industry act as a valuable insight to learners in AI. You will also find interesting freelancing tips to break into the profession.

With O’Reilly’s blog, it’s easy to stay on top of the industry trends as their posts often come from leading AI and ML influencers. It will help you understand how artificial intelligence and machine learning are implemented by businesses, giving you the inspiration and tools you need to make sure your business remains relevant.

The machine learning blog at Carnegie Mellon University, ML at CMU, provides an accessible, general-audience medium for researchers to communicate research findings, perspectives on the field of machine learning, and various updates, both to experts and the general audience. Posts are from students, postdocs, and faculty at Carnegie Mellon.

πŸ‘‰ AI Summer

AI Summer is a free educational blog with one single purpose. To help you learn everything you need to know about Deep Learning. If you want to become a Machine Learning Expert, a Data Scientist or simply stay updated on the latest trends in the field, this is the site for you.

πŸ‘‰ Becoming Human

This blog contains the Information and Tutorials specifically on Artificial Intelligence, Machine Learning. You will find all the AI concepts in detail here with all the recent developments in the field and how it can benefit humans.

πŸ‘‰ Paperspace Blog

A Blog dedicated to Machine Learning, Artificial Intelligence, Deep Learning, Computer Vision and Natural Language Processing

Instacart’s three-million-order data set remains a Kaggle-competition go-to and a handy resource for anyone diving into product purchasing analysis. So perhaps it’s no surprise that the grocery service’s tech blog sports some thoughtful, instructive peeks behind the curtain into its work in machine learning and data science.

TechXplore covers latest news and reseach on Artificial Intelligence and Machine Learning. Join them and get insights like "Artificial nervous system uses light sensing to catch objects like humans do", "New machine learning method accurately predicts battery state of health", "DeepONet: A deep neural network-based model to approximate linear and nonlinear operators" and more.

πŸ‘‰ MIT Tech Review

MIT is no doubt the leading research institute for technology. They have dedicated a complete section on their website for artificial intelligence enthusiasts.

Every now and then they share research material about how a machine can learn and improve our lives. Articles like machine learning model that can reason about everyday actions and helping autonomous vehicles see around corners signify the capabilities of intelligent systems.

πŸ‘‰ I'm a Bandit 

This blog is about various topics that Sebastien find interesting, essentially in optimization, probability and statistics. The blog is backed by Sebastien Bubeck, A Microsoft researcher, whose main focus lies in the mathematics of machine learning. A glimpse to his latest covers includes A law of robustness for neural networks, Provable limitations of kernel methods, Memorization with small neural networks and more

Developing artificial intelligent programs is a very complex and time-consuming task. As a programmer, they often stuck in difficult coding challenges that slow down our progress.

That’s why IBM took the initiative to create a platform called Code Patterns to solve commonly faced problems by developers. They write about the best practices of working with machine learning models, data visualization, speech recognition, and everything related to the programming world.

πŸ‘‰ Facebook AI Blog 

Facebook AI is known for working on state-of-the-art research in the field. Their research areas focus on computer vision, conversational AI, integrity, NLP, ranking and recommendations, systems research, machine learning theory, speech, and audio, along with human and machine intelligence. The Facebook AI Blog encompasses excellent content, from blog posts to research publications.

It is similar to medium machine learning but this page will provide you helpful and interesting articles by experts from all over the world in Deep Learning.

πŸ‘‰ DataFlair

If you're searching for artificial intelligence, machine learning, data science or programming related tutorials then DataFlair can help you. They covers wide range of articles like "Top 47 Machine Learning Projects for 2021 - Source Code Included", 70+ Data Science Project Ideas and Datasets", Artificial Intelligence vs Machine Learning vs Data Science vs Deep Learning", "Best Machine Learning Case Studies" and more

Analytics Vidhya is always ranked among the best learning points for data science and machine learning students. It’s like a one-stop-shop that offers good articles, a discussion forum, and some free courses. It even enables companies to hire top-notch talent by organizing competitions.

Where Microsoft uses Artificial Intelligence in their products as well as in other stuffs. This blog will explore the insights like "See How Microsoft PowerPoint’s AI-powered coach will hone your presentation skills everywhere", "The science behind semantic search: How AI from Bing is powering Azure Cognitive Search", "With reinforcement learning, Microsoft brings a new class of AI solutions to customers" and more

The Gradient is a digital magazine that aims to be a place for discussion about research and trends in artificial intelligence and machine learning. They provide accessible and technically informed overviews of the what's going on AI, as well as a platform for perspectives on recent developments and long-term trends.

At Off Convex, The authors will report on interesting research directions and open problems, and highlight progress that has been made in convex optimization. They aims to generate an active dialog between theorists, scientists and practitioners and to motivate a generation of young researchers to work on these important problems.

Microsoft’s Machine Learning blog is a resource that can serve many purposes. Structured as a simple list of articles ordered by the date it contains posts about how Machine Learning can improve business, where no tech background is needed, to articles about Deep Learning.


Journal of Machine Learning Research website provides the papers published in the journal from 2000 onwards freely online, bringing high quality ML research papers to the public. Starting from October 2000, 20 volumes have been published on the website, with each containing anywhere from 50-100 research papers on Machine Learning

πŸ‘‰ FastAI

FastAI is known for his awesome deep learning courses. Apart from courses, you can also find news and informative article on their blog. The blog is managed by Jeremy Howard and Rachel Thomas. Some of their latest covers includes "I violates a code of conduct", "fast.ai releases new deep learning course, four libraries, and 600-page book" and more

πŸ‘‰ Skynet Today

Skynet Today is a site dedicated to providing accessible and informed coverage of the latest AI news and trends. They offer a platform for people with expertise in AI to share their knowledge and perspectives with a broader audience. Regardless of how much you understand the inner workings of computers and today’s AI algorithms, as long as you are interested in being informed about the state of AI – without the hype and misinformation – their articles are meant for you.

πŸ‘‰ Daniel Seita

Daniel Seita is a computer science PhD student at the University of California, Berkeley, working on robotic manipulation and machine learning as part of Berkeley Artificial Intelligence Research (BAIR). On his Github blog, he had written more than 300 articles on a variety of topics. Latest stories from his blog includes "Inverse Reinforcement Learning from Preferences", "Getting Started with SoftGym for Deformable Object Manipulation" and more. 

πŸ‘‰ Neptune AI

Neptune.AI provides a remarkable machine learning blog, offering tutorials on machine learning modeling, hyperparameter optimization, model evaluation, data exploration, generative models, machine learning tools, and many more. Neptune.AI also offers a framework that makes it easier to track versions of your Jupyter notebooks, helps with managing your experimentation process, and integrates with your team’s workflow easily.

πŸ‘‰ LearnOpenCV

This blog is for programmers, hackers, engineers, scientists, students and self-starters who are interested in Computer Vision and Machine Learning. Join LOC and learn computer vision, machine learning, and image processing with OpenCV, CUDA, Caffe examples and tutorials written in C and Python.

In this blog, you will find out Everything on AI, including futuristic robots, computer-based models, AI-related innovations and discoveries, and much more.

πŸ‘‰ Stanford AI

The Stanford Artificial Intelligence Laboratory (SAIL) has been a center of excellence for Artificial Intelligence research, teaching, theory, and practice since its founding in 1962. They write about latest research ongoing in Stanford, different guides, news, talks and resources related to Artificial Intelligence and Machine Learning.

πŸ‘‰ DeepLearning AI

Stay up to date with nuanced takes on high-impact business trends, practical research papers, and industry-shaping applications with the batch of DeepLearning.AI. Every week, the Batch presents the most important AI events and perspective in a curated, easy-to-read report for engineers, enthusiasts, and business leaders as well as a personal note from Andrew Ng.

πŸ‘‰ AI Trends

AITrends is focused on AI in the enterprise. They cover the major areas of AI, including predictive analytics, deep learning, big data, cognitive computing, machine learning, cloud, and more. This AI blog is specifically useful for businesses who want to stay on top of everything that AI is coming up with to enhance how businesses operate.


Machine Intelligence Research Institute (MIRI) is dedicated to ensuring we all understand the positive impact of AI replacing human intelligence in most aspects of life. They have newsletters that you can subscribe to or go to the website to check out what latest conversations have happened and with whom or read their research on pressing AI developments.

πŸ‘‰ Lex Fridman

Lex FridMan is a researcher for human-centered AI, autonomous vehicles, and deep learning at MIT. His blog is a one-stop site for ways to listen to his podcast. He brings in people who specialize in deep learning, robotics, AGI, neuroscience, philosophy, psychology, cognitive science, economics, physics, mathematics, and more. These discussions will help you broaden your understanding of the big picture of AI at current times.

KΓ‘roly Zsolnai-FehΓ©r is the brilliant mind behind this popular channel that introduces new science researches, particularly Artificial Intelligence and Machine Learning. The site releases new content every week and has attracted 933K subscribers. It seems like no matter how complicated the theory in a jargon-dense study, Two Minute Papers can always find a way to deliver a video that breaks down the details in the time it takes to eat an apple.

Analytics India Magazine chronicles technological progress in the space of analytics, artificial intelligence, data science & big data by highlighting the innovations, players, and challenges shaping the future of India through discussion of ideas and thoughts by action-oriented individuals who want to change the world.

πŸ‘‰ Hackernoon / AI

Hackernoon, a micro organization with 15K creative writers who writes on various topics including artificial intelligence, machine learning and data science. Some of their latest post includes "How To Get Started With Machine Learning: A Tutorial For Beginners By A Beginner", "Machine-Learning Neural Spatiotemporal Signal Processing with PyTorch Geometric Temporal", "How AI Can Help You Make Your Videos Amazing" and more. 

πŸ‘‰ Underfitted

Every week, Santiago shares one story that tries really hard not to be boring and teach you something new about machine learning. The aim behind creating this blog is to cover as well as convert theoretical machine learning to practical machine learning. The newsletter is new but the articles are amazing and the blog is consistent and active. No complex math, no theory, only practical machine learning in a fun way. 

You won’t find a recipe for Spotify’s recommendation-system secret sauce-a hybrid of content-based and collaborative filtering that’s been crucial to the streaming app’s success-on the company’s blog. But deep-dive contextual explainers of Spotify’s various frameworks-like Lexikon, for data discovery, and its new “The Experimentation Platform,” a more data-friendly alternative to traditional A/B testing-are reliably informative reads. 

Tim Vieira, at graduate descent covers in-depth articles on math for machine learning, statistics, algorithms, reasoning, data structures and more. If you're math plus machine learning guy then this blog is for you. Some of his latest releases includes "Fast rank-one updates to matrix inverse?", "On the Distribution of the Smallest Indices" "On the Distribution Functions of Order Statistics" and more.

πŸ‘‰ Serokell

Serokell is a beginner type machine learning blog where you will find basic articles like "How to participate in Kaggle Competition", "17 Free Resources to help you learn Machine learning in 2021", "Top 10 ideas for your machine learning projects in 2021", "A Guide to Deep Learning and Neural Networks" and more. If you're a newbie and looking for resources and beginners intro type articles, then you should check this blog

πŸ‘‰ H2O.ai Blog

At H2O.ai blog, the author writes news related to implementation of their software in various business, share opinions on questions like "Successful AI: Which Comes First, the Data or the Question?", explores amazing journeys like "Meet the Data Scientist who just cannot stop winning on Kaggle" and more.

One of the best source to follow for latest artificial intelligence news. Some of their recent stories include "Study: People trust the algorithm more than each other", "Physicists working with Microsoft think the universe is a self-learning computer", "Intel’s new AI helps you get just the right amount of hate speech in your game chat" and more. From the title, If you think it will be interesting source then follow them.

πŸ‘‰ Chip Huyen

Chip Huyen, a former NVIDIA Senior Deep Learning Engineer and a lecturer at Stanford University has created this blog to share her experience as well essential stuffs. Take a look at some of her recent articles that includes "Machine learning is going real-time", "Course announcement - Machine Learning Systems Design at Stanford!", "What I learned from looking at 200 machine learning tools" and more. In short, A must follow blog.

This blog will take you inside LinkedIn. What, why and how they use AI, ML and Data Science to build as well as to solve various problems. Latest stories on their blogs includes "Using the LinkedIn Fairness Toolkit in large-scale AI systems", "Dagli: Faster and easier machine learning on the JVM, without the tech debt", "Building a heterogeneous social network recommendation system" and more

πŸ‘‰ Adam Geitgey

Adam Geitgey is a former Software Developer at Groupon and an author at Lynda. He believes ML is integral to the future of software and that developers should have a strong working knowledge, so he provides guides and techniques to help them develop and grow. On his Medium blog, he covers the tenets of ML through interactive tutorials and practical examples, which make it easier to see the useful applications to different businesses and industries.

As the name suggest, the founder of this AI medium publication has created this blog to break complexity of AI and explain it in the simple form. Some of their latest release includes "Deep Q-Learning Simply Explained", "Discrete Math — The Basics of Lexical Analysis: From NFA to DFA", "Creating Your First Neural Network With PyTorch", "Case Study: Breast Cancer Diagnosis" and more 

πŸ‘‰ Stanford HAI

The last as well as another must follow AI blog from Stanford's HAI (Human Centered Artificial Intelligence). The contributors writes on real life examples and implementation and impact of AI in various fields. Join this Artificial Intelligence Blog and see the perspective of professionals by reading their articles. Some of their latest covers are "How will AI transform traditional industries?", "How AI Can Augment Health Care: Trends To Watch", "AI in Education: Augmenting Teachers, Scaling Workplace Training", "Artists’ Perspective: How AI Enhances Creativity and Reimagines Meaning" and more.

Active Wizards is a team of experienced data scientists and engineers focused on complex data projects. Apart from solving complex problems, they also shares their journey as well as basic and intermediate type machine learning articles on their blog. Some of their recent covers include "5 Real-world Examples of Logistic Regression Application", "Sentiment Analysis with Naive Bayes and LSTM", "Machine Learning Mindmap", "Top 8 Google AI Tools" and more.

Hope this huge list of machine learning blogs, computer vision blogs, deep learning blogs and artificial intelligence blogs will be helpful for you. If you think this list of  can be helpful to others, please share it with other needed ones as well as with your friends. And if you have any feedback or request regarding this article or next blog, you can tell us via blogger contact form or DM us on any of our social media accounts. Follow berkeley deep reinforcement learning, uc berkeley machine learning, colah blog, cmu statistics and machine learning, machine learning at berkeley, reddit machine learning, reddit learn machine learning, reddit deep learning, reddit reinforcement learning, kaggle, medium machine learning and start learning!
July 01, 2021
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