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OverviewFull Product DetailsAuthor: Sébastien Roch (University of Wisconsin, Madison)Publisher: Cambridge University Press Imprint: Cambridge University Press ISBN: 9781009509459ISBN 10: 1009509454 Pages: 499 Publication Date: 30 September 2025 Audience: College/higher education , Undergraduate , Postgraduate, Research & Scholarly Format: Hardback Publisher's Status: Forthcoming Availability: Not yet available ![]() This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release. Table of Contents1. Introduction: a first data science problem; 2. Least squares: geometric, algebraic, and numerical aspects; 3. Optimization theory and algorithms; 4. Singular value decomposition; 5. Spectral graph theory; 6. Probabilistic models: from simple to complex; 7. Random walks on graphs and Markov chains; 8. Neural networks, backpropagation and stochastic gradient descent.Reviews'Mathematical Methods in Data Science provides a clear and accessible primer on key concepts central to data science and machine learning. Through engaging examples from neural networks, recommender systems, and data visualization, Roch illuminates myriad foundational topics and methods. Designed for readers from a broad range of backgrounds, this text is an indispensable resource for students and professionals.' Rebecca Willett, University of Chicago 'This book is an outstanding introduction to the fundamentals of data science by an expert educator and researcher in the area. Its choice of topics, its use of Python, its plentiful examples and exercises, and its battle-testing in the classroom make it a top choice for students and educators seeking a mathematically rigorous yet practical entrée into data science.' Stephen J. Wright, University of Wisconsin Author InformationSébastien 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). Tab Content 6Author Website:Countries AvailableAll regions |