Book Review: 50 ML Projects to Understand LLMs

Book Review: 50 ML Projects to Understand LLMs Amazon Author’s website I was offered to read 50 ML Projects To Understand LLMs by Mike X Cohen in exchange for an honest review. Rather than building, fine-tuning, or prompting LLMs, the book treats GPT-2 as a scientific specimen and teaches you to investigate it with code, statistics, and controlled experiments across 50 hands-on projects. As I have spent a lot of time working on model validation and LLM evaluation, I liked that the author focuses on the statistical discipline throughout the book — permutation tests, multiple-comparison corrections, control baselines, manipulation checks. That kind of validation rigor is what separates a real result from a lucky one both at work and in ML competitions. The overall structure The 50 projects are organized into six chapters that loosely follow the flow of data through a transformer model: Tokenization: how text becomes integers, whether tokenization is really compression, and how strongly…