Best Machine Learning Books You Should Read: 2020 Edition

Original article was published on Deep Learning on Medium

INTRODUCTORY LEVEL: Introduction To Machine Learning With Python: A Guide For Data Scientists.

It is a gentle introduction into machine learning. You don’t need any prior knowledge about python and it introduces fundamental concepts and applications of machine learning with examples.

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INTERMEDIATE LEVEL: Python Machine Learning.

Python Machine Learning

It is a great practical book with a lot of actual examples of code. It starts gently & then proceeds to a more advanced level in machine learning and deep learning.

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INTERMEDIATE LEVEL: Hands-on Machine Learning 2nd Edition.

It is an amazing reference and mid-level. It covers all the fundamentals(classification models, dimensionality reduction) and then gets into neural networks and deep learning.

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EXPERT LEVEL: Pattern Recognition and Machine Learning.

This book uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. There is no previous knowledge of pattern recognition or machine learning concepts is assumed.

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EXPERT LEVEL: Deep Learning.

It is amazing for deep learning algorithms. It doesn’t contain much code but has great insights about now one should approach problems with machine learning. This book is written by experts in deep learning. It covers virtually all currently used techniques.

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EXPERT LEVEL: Machine learning.

It’s a tour-de-force through mathematics behind all machine learning methods. You probably won’t be able to read it at once, but it’s
very useful as a reference in machine learning research.

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All these books are an awesome and outstanding piece of read to expand or to learn ML and concepts of ML. I will absolutely try to encourage you to these books.