Description

Peter Norvig, Research Director at Google, co-author of AIMA, the most popular AI textbook in the world: Burkov has undertaken a very useful but impossibly hard task in reducing all of machine learning to 100 pages. He succeeds well in choosing the topics – both theory and practice – that will be useful to practitioners, and for the reader who understands that this is the first 100 (or actually 150) pages you will read, not the last, provides a solid introduction to the field.
Aurélien Géron, Senior AI Engineer, author of the bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow: The breadth of topics the book covers is amazing for just 100 pages (plus few bonus pages!). Burkov doesn t hesitate to go into the math equations: that s one thing that short books usually drop. I really liked how the author explains the core concepts in just a few words. The book can be very useful for newcomers in the field, as well as for old-timers who can gain from such a broad view of the field.
Karolis Urbonas, Head of Data Science at Amazon: A great introduction to machine learning from a world-class practitioner.
Chao Han, VP, Head of R&D at Lucidworks: I wish such a book existed when I was a statistics graduate student trying to learn about machine learning.
Sujeet Varakhedi, Head of Engineering at eBay: Andriy s book does a fantastic job of cutting the noise and hitting the tracks and full speed from the first page.
Deepak Agarwal, VP of Artificial Intelligence at LinkedIn: A wonderful book for engineers who want to incorporate ML in their day-to-day work without necessarily spending an enormous amount of time.
Gareth James, Professor of Data Sciences and Operations, co-author of the bestseller An Introduction to Statistical Learning, with Applications in R: I would highly recommend The Hundred-Page Machine Learning Book for both the beginner looking to learn more about machine learning and the experienced practitioner seeking to extend their knowledge base.