Best Machine Learning Books You Should Read: 2020 Edition
These books cover the Introductory level to Expert level of knowledge and concepts in ML. These Books have some core factors about ML. Give them a try. Lets Start.
INTRODUCTORY LEVEL: Introduction To Machine Learning With Python: A Guide For Data Scientists.
It is a gentle introduction into machine learning. It does not assume you to know any knowledge about python and it introduces fundamental concepts and applications of machine learning with examples.
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.
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.
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.
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.
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.
All these books are an awesome and outstanding piece of read to expand or to learn ML and concepts of ML. I will definitely try to encourage you to these books.
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