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 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
 ISBN10/ASIN: 1607857464
 ISBN13: 9781607857464
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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.
Reviews, Rating, and Recommendations: Related Book Categories: Data Science and Engineering
 Probability Theory and Stochastic Process
 Python Programming
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