This list of books are ONLY the books that have been ranked on the lists that are aggregated on this site. This is not a comprehensive list of all books by this author.

1. 1. The Hundred Page Language Models Book

   

   A concise, practitioner-focused guide to large language models that explains how transformers work, how models are trained and fine‑tuned, and how to build reliable applications. It covers tokenization, attention, pretraining objectives, instruction tuning and RLHF, as well as efficiency techniques like distillation and quantization. Practical chapters address prompting, evaluation, safety and alignment, and production concerns such as retrieval‑augmented generation, tool use, agents, deployment, cost, and risk management. Written to give engineers and decision‑makers a compact, end‑to‑end understanding of the field.

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2. 2. The Hundred Page Machine Learning Book

   

   A concise, practitioner-focused primer that distills the essential concepts, algorithms, and practical advice of modern machine learning into a compact, accessible format; it covers supervised and unsupervised methods, evaluation and validation, regularization and model selection, probabilistic foundations and Bayesian thinking, optimization, neural networks and deep learning, ensemble methods, feature engineering, and deployment concerns, emphasizing intuition, key equations, and actionable tips for building and evaluating models in real-world settings.

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