Books¶
A short, opinionated shelf — not another 100-item list. Ordered by when to read them on the learning path.
Foundations¶
- Build a Large Language Model (From Scratch) — Sebastian Raschka. The best hands-on route to actually understanding transformers. Pairs with Courses 03–05.
- Deep Learning — Goodfellow, Bengio, Courville. Reference, not cover-to-cover.
- Speech and Language Processing — Jurafsky & Martin (free draft online). NLP grounding.
AI Engineering¶
- AI Engineering — Chip Huyen. The production-systems view; pairs with Courses 06–13.
- Designing Machine Learning Systems — Chip Huyen. Still the MLOps baseline.
- Prompt Engineering for LLMs — Berryman & Ziegler. Deeper than any blog post.
Agents & beyond¶
- Agent engineering is moving too fast for books — the durable material lives in papers, lab engineering blogs, and the Agent Engineering track.
Free & online¶
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