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) cover

Build a Large Language Model (From Scratch)

Sebastian Raschka

currently reading

Implements a GPT-style model end to end — tokenizer, attention, training loop, fine-tuning.
Deep Reinforcement Learning cover

Deep Reinforcement Learning

Alexander Zai and Brandon Brown

currently reading

Working through the foundations of deep RL — value-based, policy-based, and model-based methods.
Programming Massively Parallel Processors cover

Programming Massively Parallel Processors

Wen-mei W. Hwu, David B. Kirk, Izzat El Hajj

currently reading

The CUDA and GPU-architecture book — memory hierarchy, kernels, parallel patterns.
Software Design by Example (Python) cover

Software Design by Example (Python)

Greg Wilson

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 cover

Understanding Deep Learning

Simon J. D. Prince

currently reading

A unified, math-first walk through modern deep learning. PDF is freely available.

Mathematics
Introduction to Linear Algebra cover

Introduction to Linear Algebra

Gilbert Strang

currently reading

Strang's classic. Going through it alongside MIT 18.06 lectures.

Non-fiction
Everything Is Tuberculosis cover

Everything Is Tuberculosis

John Green

currently reading

How a curable disease still kills more than a million people a year, and what that says about the rest of us.