Data Science and Machine Learning Mathematical and Statistical Methods, 2nd Edition

Praise for the first edition: "In nine succinct but information-packed chapters, the authors provide a logically structured and robust introduction to the mathematical and statistical methods underpinning the still-evolving field of AI and data science." - Joacim Rocklv and Albert A. Gayle, International Journal of Epidemiology, Volume 49, Issue 6 "This book organizes the algorithms clearly and cleverly. The way the Python code was written follows the algorithm closely-very useful for readers who wish to understand the rationale and flow of the background knowledge." - Yin-Ju Lai and Chuhsing Kate Hsiao, Biometrics, Volume 77, Issue 4 The purpose of Data Science and Machine Learning: Mathematical and Statistical Methods is to provide an accessible, yet comprehensive textbook intended for students interested in gaining a better understanding of the mathematics and statistics that underpin the rich variety of ideas and machine learning algorithms in data science. New in the Second Edition This expanded edition provides updates across key areas of statistical learning: Key Features: The purpose of Data Science and Machine Learning: Mathematical and Statistical Methods is to provide an accessible, yet comprehensive textbook intended for students interested in gaining a better understanding of the mathematics and statistics that underpin rich variety of ideas and machine learning algorithms in data science.

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