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36 Machine Learning Books You Should Read in 2023

Machine Learning Books

Everyone has their own learning style, and for some, reading can be a great way to brush up on a current skill or learn something new entirely. If you’re interested in the world of machine learning (ML), there are several great books on the topic. Which one is right for you depends on how much you already know.  If you are new to ML, there are some great books designed for beginners. There are also some excellent digital machine learning ebooks available.

36 Machine Learning Books You Should Read in 2023

Are you searching for the best machine learning books to learn more about the field, broaden your understanding, or even review your knowledge and skills? We have listed the top 11 machine learning books for anyone looking to get into the business as a data science or machine learning practitioner to assist you in selecting a well-structured study path.

Each book is endorsed by Machine Learning specialists and core experts, making it the most comprehensive collection of helpful information in the Machine Learning world. Hence, let’s get started!

Best Machine learning Books for Beginners and Experts Most of the books below provide an introduction or overview of machine learning through the perspective of a particular subject area, like case studies and algorithms, statistics, or those already familiar with Python.

No matter where you are in your machine learning journey, there is bound to be a book that’s right for you. Here are some of our favorites:

36 Machine Learning Books You Should Read in 2023

Learning machine learning is easy and quick, and you can learn through machine learning courses, videos, bootcamps, tutorials, and of course, good machine learning books! Though there are claims all over the Internet that you can become a data scientist or a machine learning engineer in 30 days, ProjectPro experts suggest that you take time to sink in the foundational concepts of machine learning step by step, work on diverse machine learning projects to apply what you’ve read in a book or learned in a video.

To help you choose a well-structured learning path for machine learning, we have narrowed it down to the 21 best machine learning books and 50+ Machine Learning Projects for anyone who wants to make it big in the industry as a data science or machine learning practitioner. Each project and book is recommended by ProjectPro’s industry experts, making them the richest sources of practical knowledge in the world of machine learning. So, let’s get started!

12 Machine Learning Books You Should Read in 2023

Listed below are the best machine learning books for beginners to experts with focus areas such as PythonRDeep Learning, and Artificial Intelligence. These books will help you jumpstart your machine learning career and help you along the way. So, let us start with the best machine-learning books for beginners before moving on to complex books.

3 Best Machine Learning Books for Beginners

Here are three of the best machine-learning books for beginners:

It’s a good book for beginners who want to learn machine learning. You don’t even need a background in coding, mathematics, and statistics to start reading this book.

Exclusive Topics Covered 

  • Downloading free datasets, tools, and machine learning libraries
  • Regression Analysis
  • Data Scrubbing techniques
  • Basics of Neural Networks
  • Clustering
  • Bias/Variance
  • Decision trees
  • Building Machine Learning models

Why read this book?

The book provides precise explanations and visual examples accompanying each machine-learning algorithm. This makes the concepts more approachable for beginners to understand the fundamentals of machine learning.

Most Popular Review of the Book

“An excellent introduction to machine learning, in which the author describes what machine learning is, techniques and algorithms, and the future of & resources for machine learning learners.” – An Experienced Machine Learning Professional 

This book presents a solid introduction to machine learning in just a hundred pages. The book not just provides an understanding of machine learning concepts but also delves into the different types of it, such as supervised learning, unsupervised learning, and reinforcement learning. 

Exclusive Topics covered: 

  • Fundamental Algorithms
  • Anatomy of a Learning Algorithm
  • Deep Learning and Neural Networks
  • Unsupervised Learning
  • Basic and Advanced Practice

Why read this book? 

Several top professionals recommend this book, including Peter Norvig (Director of Research at Google), Aurélien Geron (Senior AI Engineer, author of a bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow), Karolis Urbonas(Head of Machine Learning at Amazon), and Sujeet Varakhedi (Head of Engineering at eBay).

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