Jason Brownlee's blog about learning Machine Learning for developers, as well as a range of practical examples and case studies in Machine Learning, Data Science and Deep Learning. He covers topics like neural networks and genetic programming, and publishes several times per week.
Eugene writes one of the most friendly data science blogs on the Internet. By day, he works as an applied scientist at Amazon. He also includes plenty of snippets writes articles that are readable and digestible. He also send a weekly newsletter about effective data science, machine learning, and career development.
Clojure, Machine Learning, Bayesian Data Analysis, and High-Performance Computing for programmers. Written for programmers who would like to learn AI from programming perspective. 100% Clojure. The author is an university professor, but the blog is 100% practically oriented. Dragan is the author of several Clojure AI software libraries and the Interactive Programming for Artificial Intelligence book series.
Chris is the Director of Machine Learning at the Wikimedia Foundation. He has spent over a decade applying statistical learning, artificial intelligence, and software engineering to political, social, and humanitarian efforts. He is the author of the acclaimed "Machine Learning Flashcards".
This blog covers data projects, from Bayesian recommenders to deep learning to data mining. Vincent is a self-taught developer and data scientist, currently living in the Netherlands. He's also the fo-founder and co-chair of PyData Amsterdam.
Victor writes about web development with tools like Gatsby and machine learning with tools like Keras. He also has recent posts about security, type safety, and web performance.
Mixed posts about electronic projects as well as server infrastructure, encryption, homelabs and even about teaching. Sometimes tales about finding malicious devices in customer networks (and how to dissect them) as well as government hacks brought out by whistleblowers contacting Christian directly.
Python, Data Science, and Machine Learning Tutorials written by Renan Moura. There's an extensive backlog of posts for anyone looking to go deeper into Python and find practical ways to apply it in the fields of data science and machine learning.
Tobias writes about machine learning and data science in python with a specific focus on natural language processing. On this blog, he regularly shares interesting ideas and methods that came up in his day-to-day work as a freelance data scientist. One signature of the articles is, that all code needed to reproduce the examples is shown and easily accessible.
Ines covers her work on with Python, Artificial Intelligence, and Natural Language Processing (NLP) topics. She's the cofounder of Explosion and a core developer of spaCy and Prodigy.
Julien writes about working with AWS and Machine Learning. On his blog you'll find articles on topics like using Amazon SageMaker, updates from re:Invent, and working with TensorFlow using Amazon services.
This blog covers the research paper summaries of the ground breaking papers in the field of Deep Learning. The goal is to cover the most important parts of these famous paper, so if someone doesn't have enough time to go through the paper, the blog post can help them gain a fair idea of the model/approaches.
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Acknowledgements — Thanks to Hero Patterns and Devicon for SVG assets used on this site. Plus, thanks to everyone who's submitted their favorite blogs so far! We'd love your suggestions for how to make this list better on Twitter, @bloggingfordevs.
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