This article showcases our top picks for the Best Machine Learning Books. We reached out to industry leaders and experts who have contributed the suggestions within this article (they have been credited for their contributions below).
We are keen to hear your feedback on all of our content and our comment section is a moderated space to express your thoughts and feelings related (or not) to this article This list is in no particular order.
This product was recommended by Zach Hendrix from GreenPal
Great introductory book that covers many key concepts in a simple, easily digestible format. This is the first book I read on the concept of Machine Learning based on a recommendation from a mentor. The book, along with additional online materials, helps build a solid foundation from which to grow from.
This product was recommended by Zach Hendrix from GreenPal
You will probably get a few recommendations for this one as it’s an Amazon Bestseller on the subject. In short, pun-intended, it is a fantastic condensed version of key concepts. Concise, no fluff explanations and examples on a wide range of topics.
This product was recommended by Zach Hendrix from GreenPal
This is a great look into real world application and life-cycle. Hands-on, step-by-step guide to planning, building, evaluating, and deploying actual Machine Learning applications.
This product was recommended by James Idayi from Cloudzat
This is a 2-books-in-1 series that can’t be missed! This book covers the very basics on Machine Learning and guides you through an intricate path in learning about all you need to know to be your resident expert in Machine Learning and more. From your first introductions to these complicated topics, to being well on your way to starting a career in the Machine Learning space, Ander Park’s set of 2 books are a great way to become informed on this subject!
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