Machine learning blogs and other publications I think are worth reading regularly.

Current Favourites // Organisations // Great Reads // Well-Known Authors // Cognitive Science

Personal Favourites

• Lilian Weng’s Blog - Amazing posts on machine learning from a research scientist at OpenAI
• inFERENCe by Ferenc Huszár - Posts on machine learning, statistics and opinions on readings
• Lei Mao’s Blog - Practical, short posts on deep learning, statistical inference and implementation.
• Gregory Gundersen’s Blog - Highly detailed, clear posts on statistical machine learning and scalable Bayesian inference from Gregory Gundersen.
• Xavier Bourret Sicotte’s Blog - Python notebooks with theory delving into typical machine learning techniques
• Michael Betancourt’s Blog - Very in-depth posts on e.g. Hierarchical Modelling or the Relationships between Probability Distributions
• Jay Alammar’s Blog - Excellent in-depth posts about NLP and machine learning in general.
• Christopher Olah’s Blog - The one and only Colah’s blog.
• Artem Golubin’s Blog - Artem Golubin writing on machine learning, NLP and Python.
• Michael Nielsen’s Main Blog and Data-driven Intelligence Blog - Posts on causality, deep learning, computer science and more.
• Andrej Karpathy’s Blog and Andrej Karpathy’s Medium

Organisations

• DeepMind’s Blog
• Google AI’s Blog and Google AI Research
• Facebook AI’s Blog and Facebook AI Research
• OpenAI Blog
• Uber’s Engineering Blog
• Spotify’s Engineering Blog and specifically, their Machine Learning and Data Science posts.
• Distill

Great Reads

• Eli Bendersky’s Blog - Posts on mathematics, computation and statistics.
• While My MCMC Gently Samples - Posts by Thomas Wiecki (PyMC founder) on Bayesian statistics with implementation in Python including with PyMC
• Stanislav Fort’s Blog - Cool mind-bending, mathsy posts from a guy finishing his PhD in Stanford’s Neural Dynamics and Computation Lab
• Count Bayesie - Really good in-depth posts on (not only Bayesian) statistics.
• John Myles White’s Blog - Posts on statistics and computing by the co-author of Machine Learning for Hackers.
• Noam Ross’ Blog - Posts on disease ecology and statistics.
• Chris McCormick’s Blog - Posts on machine learning and later many on natural language processing.
• Bounded Rationality by Brian Keng - Technical posts on machine learning and deep learning.
• Andrew Trask’s Blog - Posts on machine learning and neural networks from Andrew Trask of DeepMind.
• Matthew N. Bernstein’s Blog - Pieces on linear algebra, information theory and algorithms for statistical inference.
• Explained Visually - Visual explanations of concepts from machine learning.
• Machine Thoughts by Prof David McAllester - Technical posts on machine learning and artificial intelligence.
• Kristoffer Magnusson’s Blog - Posts on psychology and statistics.
• Julia Silge’s Blog - Posts on wacky applications of statistics using the R language.
• Andrew Brooks’ Blog - Practical posts on mathematical and deep learning problems.
• Michael Clark’s Blog - Posts on statistics with code and visualisations.
• Causal Analysis in Theory and Practice - The UCLA Causality blog often co-written by Judea Pearl.

Well-Known Authors

• Stephen Wolfram Writings - Considered and rich posts from Stephen Wolfram.
• Columbia Statistics Blog - Posts on diverse applications of statistics mainly from Andrew Gelman, but also others at Columbia’s department of statistics.
• Cleve’s Corner - Posts from Cleve Moler, creator of MATLAB, on mathematics and computing.

Cognitive Science

• xcorr Patrick Mineault’s blog on computational neuroscience, machine learning and the crosstalk between the two research fields.
• Angela D. Friederici’s Lab’s publications on neurocognitive processing of language.
• Christian Doeller’s Lab publications on spatial cognition, memory and decision making.
• Language: Latest Research and Reviews in Nature - The latest research publications and review articles on language published in Nature usually with a slant towards cognitive science.