Books
Books I am reading, have read, or have set down for now. Technical ones get notes; the rest just live here as covers I'd recommend (or wouldn't).
Technical
Build a Large Language Model (From Scratch)
currently reading
Implements a GPT-style model end to end - tokenizer, attention, training loop, fine-tuning.
Deep Reinforcement Learning
currently reading
Working through the foundations of deep RL - value-based, policy-based, and model-based methods.
Programming Massively Parallel Processors
currently reading
The CUDA and GPU-architecture book - memory hierarchy, kernels, parallel patterns.
Software Design by Example (Python)
currently reading
Builds tools (a build system, a parser, a debugger…) from scratch in Python to teach how the tools you use every day actually work.
Understanding Deep Learning
currently reading
A unified, math-first walk through modern deep learning. PDF is freely available.
