Hands-On Large Language Models Book Explains LLMs With 300 Illustrations
The book devotes an entire track to embedding-based applications — classification, clustering, semantic search and training your own embedding models — which most LLM books skip in favour of generation. Practitioners building RAG pipelines or fine-tuning encoder models can follow its open-source code directly. Alammar's Illustrated Transformer explanations have been standard university course references since 2018, so this is a systematically structured successor to material many already know.
