Textbook Recommendation: An Introduction to Statistical Learning with Applications in Python
A practical resource to learn applied statistics, data science, and machine learning
If there is one book that I recommend to learn applied statistics, it is "An Introduction to Statistical Learning with Applications in Python" by Gareth James, Daniela Witten, Rob Tibshirani, Trevor Hastie, and Jonathan Taylor.
It provides clear and intuitive explanations without diving too much into mathematical detail.
It covers the essential techniques for supervised and unsupervised learning that you need to work in applied statistics, data science, and machine learning.
It provides many examples in Python, the most popular programming language for data science today.
It covers data science and machine learning with statistical rigour.
For many years, this book had examples in R. Thus, I was pleasantly surprised to find a new version of the book in Python; the authors invited Jonathan Taylor of Stanford University to contribute to this edition. Python is the programming language that employers seek the most in data and analytics, so it is important for statistics students to learn Python, even if their academic instructors do not use it.
This book is freely available as a PDF file.