Author of the best-selling practical ML textbook
Aurélien Géron
Profile
Aurélien Géron wrote the book that’s probably on your desk if you’re learning ML by building. “Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow” — now in its third edition through O’Reilly — is the most-read practical ML textbook in the world, translated into more than a dozen languages, and the go-to recommendation for people who want to actually ship something rather than just read papers. It became a standard reference by doing something most ML books don’t: working code you can run, clear explanations without math-anxiety, and an honest progression from linear regression to transformers.
Before the book, Géron had the kind of career that makes the writing make sense. He led YouTube’s video classification team at Google from 2013 to 2016 — the team building the systems that figure out what a video is actually about. Before that he was the founder and CTO of Wifirst, a leading wireless ISP in France, and a co-founder of Polyconseil. Earlier still: engineer at JP Morgan, Société Générale, Canada’s DOD, and a stint on blood-transfusion software. He’s also a former CS lecturer who had previously written technical books on C++, WiFi, and internet architectures before ML became his thing.
In 2025 he released “Hands-On Machine Learning with Scikit-Learn and PyTorch” — a full rewrite for the PyTorch-and-Hugging-Face world that actual practitioners now live in. It’s the same pedagogical approach (build it, understand it, move on) applied to the modern stack, covering transformers and diffusion models alongside the fundamentals. His GitHub hosts the companion notebooks, which are worth studying on their own.
Géron isn’t a celebrity researcher or a thought-leader-in-residence. He’s an engineer who happens to be an exceptional explainer, and he writes like someone who has actually shipped things. If you’re the father in this duo, his book is how you close the theory gap without drowning in math-first textbooks. If you’re the son, it’s how you connect the formalism you already know to systems that run.
Books
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (3rd Edition) The canonical practical ML textbook — end-to-end projects from linear regression to transformers, with runnable notebooks for every chapter. Hands-On Machine Learning with Scikit-Learn and PyTorch The 2025 rewrite for the PyTorch + Hugging Face stack, covering transformers and diffusion models alongside the fundamentals.Videos
Spotify Podcasts
