Test Bundle

End-to-end retrieval-augmented generation: chunking strategies, embeddings, hybrid search, reranking and evaluation — with full pipeline diagrams.

Everything a working developer needs in Python for AI: environments, NumPy, data pipelines, notebook workflows and the libraries the AI stack actually uses.

How large language models really work: tokenisation, pretraining objectives, instruction tuning, RLHF and decoding strategies, explained visually.