6 of the Best Statistics Books for Machine Learning

Statistics are the foundation of machine learning.

Having a solid understanding of the fundamentals of statistics will help you to understand and implement machine learning algorithms effectively. There are plenty of books on statistics for machine learning practitioners.

Understanding statistics will also allow you to understand better which ML algorithm is most appropriate for your problem.

Knowing all of this, and not having studied statistics in many years, I decided to reach out to the experts.

I decided to ask the Reddit r/learnmachinelearning community for the best statistics books for machine learning.

Let me tell you the community did not disappoint!

You can access the original post and responses here.

However, for the sake of ease, I have summarised the recommended statistics books for machine learning below.

1. An Introduction to Statistical Learning

• Author: Gareth James, Daniella Witten, Trevor Hastie, and Robert Tibshirani
• Price: $75.99 on Amazon
• Overview: From the Amazon product description: ‘An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years.’
• Star Rating: 4.6/5 on Amazon

2. The Elements of Statistical Learning

• Authors: Jerome Friedman, Trevor Hastie, and Robert Tibshirani
• Price: $64.10 on Amazon
• Overview: From the Amazon product description: ‘This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics.’
• Star Rating: 4.1/5 on Amazon

3. Probability and Statistical Inference

• Author: Robert V. Hogg, Elliot Tanis, and Dale Zimmerman
• Price: $185 on Amazon
• Overview: From the Amazon product description: ‘Written by three veteran statisticians, this applied introduction to probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation.’
• Star Rating: 4.8/5

4. All of Statistics

• Author: Larry Wasserman
• Price: $78.21 on Amazon
• Overview: From the Amazon product description: ‘Taken literally, the title “All of Statistics” is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory text on mathematical statistics. This book is for people who want to learn probability and statistics quickly.’
• Star Rating: 4.6/5 on Amazon

5. Mathematical Statistics with Applications

• Author: Dennis Wackerly, William Mendenhall, and Richard Scheaffer
• Price: $165 on Amazon
• Overview: From the Amazon product description: the book ‘present(s) a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world.’
• Star Rating: 3.4/5 on Amazon

6. Introduction to Mathematical Statistics

• Author: Robert V. Hogg, Joseph W McKean, and Allen T. Craig
• Price: $19.95
• Overview: From the Amazon product description: ‘Introduction to Mathematical Statistics, Seventh Edition, offers a proven approach designed to provide you with an excellent foundation in mathematical statistics’
• Star Rating: 3.4/5 on Amazon

As a bonus, on top of these statistics books for machine learning, you can also get some practice with these free online tutorials.

There are plenty of questions here to help you solidify your understanding of statistics.

Ready to get started with Machine Learning Algorithms? Try the FREE Bootcamp

That ends this article on the best books on statistics for machine learning enthusiasts.

So, now you have an understanding of statistical principles, you’re ready to start machine learning!

Check out this post on how to choose your perfect machine learning course with python.

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