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