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Mathematical Methods in Data Science: Bridging Theory and Applications with Python (Cambridge Mathematical Textbooks) - Hardcover
Book 23 of 24: Cambridge Mathematical Textbooks
Synopsis
Explore the mathematics of data science with this advanced undergraduate and graduate text integrating theory with applications in Python.
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About the Author
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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Mathematical Methods in Data Science: Bridging Theory and Applications with Python (Cambridge Mathematical Textbooks)
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Mathematical Methods in Data Science
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Mathematical Methods in Data Science : Bridging Theory and Applications With Python
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Mathematical Methods in Data Science : Bridging Theory and Applications With Python
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ISBN 10: 1009509454
ISBN 13: 9781009509459
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Mathematical Methods in Data Science (Hardcover)
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ISBN 10: 1009509454
ISBN 13: 9781009509459
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Hardcover. Condition: new. Hardcover. 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. A hands-on textbook for advanced undergraduates and beginning graduate students in data science, offering an accessible introduction to the essential mathematics behind modern data analysis. With practical Python examples and hundreds of exercises and problems, it's an invaluable resource for students and educators alike. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781009509459
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Mathematical Methods in Data Science : Bridging Theory and Applications With Python
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ISBN 10: 1009509454
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Mathematical Methods in Data Science : Bridging Theory and Applications With Python
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Mathematical Methods in Data Science (Hardcover)
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ISBN 10: 1009509454
ISBN 13: 9781009509459
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Hardcover. Condition: new. Hardcover. 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. A hands-on textbook for advanced undergraduates and beginning graduate students in data science, offering an accessible introduction to the essential mathematics behind modern data analysis. With practical Python examples and hundreds of exercises and problems, it's an invaluable resource for students and educators alike. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781009509459
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