This is a collection of things I have read that led to enjoyment or learning, and thus wanted to note down for future reference. Some are things that I have not read yet, but think will be enjoyable or valuable.
Things on the internet:
- jsomers.net | I should have loved biology
- Main Content | Jeremy Kun
- GPT in 60 Lines of NumPy
- An Intuition for Attention
- The Annotated Transformer
- Neural network training makes beautiful fractals | Jascha’s blog
- colah’s blog
- projects | Bones
- Sorta Insightful | Alex Irpan
- Deep Generative Models | CS 326 Notes
- Lil’Log | Lilian Weng
- An Opinionated Guide to ML Research
- Neel Nanda
- On Those Undefeatable Arguments for AI Doom
- ~agentydragon/How I got to OpenAI
- KL is All You Need
Books:
- Linear Algebra Done Right
- The Algorithm Design Manual
- Understanding Deep Learning
- Deep Learning - Foundations and Concepts
- An Infinite Descent into Pure Mathematics
- A Programmer’s Introduction to Mathematics
- Poor Charlie’s Almanack
- The Napkin
- Nonlinear Dynamics and Chaos
- Alice’s Adventures in a Differentiable Wonderland — Volume I, A Tour of the Land
Papers:
- Relational NN
- Minimum Description Length Principle
- [Autodidax: JAX core from scratch](https://jax.readthedocs.io/en/latest/autodidax.html
- Automatic Gradient Descent: Deep Learning without Hyperparameters
Other:
Compilations: