• Title: Introduction to Probability for Data Science
• Author(s) Stanley H. Chan
• Publisher: Michigan Publishing Services (November 5, 2021)
• Hardcover/Paperback: 704 pages
• eBook: HTML and PDF
• Language: English
• ISBN-10/ASIN: 1607857464
• ISBN-13: 978-1607857464
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Book Description

This book is an introductory textbook in undergraduate probability. It has a mission to spell out the motivation, intuition, and implication of the probabilistic tools we use in science and engineering. The writer has distilled what he believes to be the core of probabilistic methods. The author put the book in the context of data science to emphasize the inseparability between data (computing) and probability (theory) in our time.

It puts the probability in context with excellent examples from everyday science applications. The book presents examples in both Matlab and Python.

The book is a very good introduction for probability theory. In addition, it provides insightful explanations on those previous topics required for machine learning courses.

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• Data Science and Engineering
• Probability Theory and Stochastic Process
• Python Programming
• MATLAB Programming

• Introduction to Probability for Data Science (Stanley H. Chan)
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