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Mathematical Methods in Data Science

By Sébastien Roch

Mathematical Methods in Data Science

By Sébastien Roch

0 - Default Title
Description
Bridge the gap between theoretical concepts and their practical applications with this rigorous introduction to the mathematics underpinning data science. It covers essential topics in linear algebra, calculus and optimization, and probability and statistics, demonstrating their relevance in the context of data analysis. Key application topics include clustering, regression, classification, dimensionality reduction, network analysis, and neural networks. What sets this text apart is its focus on hands-on learning. Each chapter combines mathematical insights with practical examples, using Python to implement algorithms and solve problems. Self-assessment quizzes, warm-up exercises and theoretical problems foster both mathematical understanding and computational skills. Designed for advanced undergraduate students and beginning graduate students, this textbook serves as both an invitation to data science for mathematics majors and as a deeper excursion into mathematics for data science students.
Product details
Number of Pages:
582
Release Date:
2025-08-31
Publication Date:
2025-09-23
Publisher:
Cambridge University Press
Languages:
Original: English
ISBN10:
1009509454
ISBN13:
9781009509459
Weight:
1275 g
Height:
183 cm
Width:
260 cm
Thickness:
36 cm
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