Blogs
- Owen Lynch - haskell, tensor
- Jethro Kuan - org roam
- Harry Schwartz - org mode
- Gabriel Lebec - lambda calculus
- Ovid: what to know before debating type systems
- Chris Done – haskell
- Ruslan Spivak - compilers and interpreters
- Edsko de Vries - types
- Victor Zhou - AI and games
- Andy Jones - princeton - stats and inference
- Al Hassy - typed lisp
- Ryan Moulton - Information theory, learning
- composing programs
- mat palm - list of ML books
- The gradient – machine learning op eds
- Neptune AI
- Ben Lynn - functional programming
- five minute stats
- E dunham - FOSS
- karlie coss - nice brain dump
- astral codex ten
- nayuki – programming implementations of CS basics
- ribbon farm
- Christopher Olah - machine learning explained well
- Daniel Takeshi – berkeley RL blogger
- Lilian Weng – NLP concepts blogger
- Sebastian Ruder – NLP frontier
- Jay Alamar – NLP explained visually
- Christopher Wink – Linguistics
- Tim Viera – gumbel max
- Emma Benjaminson – gumbel softmax
- Soroush Khanlou – software
- Matt Zucker – robotics and graphics
- Ada Palmer – history
- Gwern – lots of tech opinions. very nice zettel-like website.
- distill ai – small set of curated blog posts and illustrated papers
- Gregory Gundersen – math/ml research blog
- brian callahan – assemblers and compilers
- steve losh – paper free
- Troels Henriksen – haskell
- Quanquan Liu – complexity, theory
- Alexander Obenauer – personal computing
- Generalist Academy – one person's notes on everything they find interesting: art, history, philosophy, science
- Boris Marinov – category theory and cs
- Julia Evans – programming. very rich blog archive
- omniglot – wiki of languages
- Jacob Tobin – stats and PL
- Dan Luu – general career advice
- Flowing Data by Nathan Yau – data visualization
- eric jang – machine learning
- ian henry – nix
- viral instruction – julia and rust
- brandur – learning rust
- lena voita – nlp
- carol chen – ml, python
- zach duey – stats, software
- denise yu – software
- freerangestatistics – stats
- SAIL blog – stanford ai
- ejmastack – arch, neovim, latex
- richard gao – comp neuroscience
- casey chu – machine learning
- slater stich – tech
- gregory gunderson – cs, machine learning
- piotr migdal – ml
- Tanishq Kumar – machine learning