Mathematical Methods in Data Science: Bridging Theory and Applications with Python (Cambridge Mathematical Textbooks) - Tapa dura

Roch, Sébastien

 
9781009509459: Mathematical Methods in Data Science: Bridging Theory and Applications with Python (Cambridge Mathematical Textbooks)

Sinopsis

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.

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Acerca del autor

Sébastien Roch is a Vilas Distinguished Achievement Professor of Mathematics at the University of Wisconsin, Madison. At UW-Madison, he helped establish the Data Science Major and has developed several courses on the mathematics of data. He is the author of Modern Discrete Probability: An Essential Toolkit (2023).

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Otras ediciones populares con el mismo título

9781009509404: Mathematical Methods in Data Science: Bridging Theory and Applications with Python (Cambridge Mathematical Textbooks)

Edición Destacada

ISBN 10:  1009509403 ISBN 13:  9781009509404
Editorial: Cambridge University Press, 2025
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