Mathematical Methods in Data Science (Paperback)
Sebastien Roch
Sold by Grand Eagle Retail, Bensenville, IL, U.S.A.
AbeBooks Seller since 12 October 2005
New - Soft cover
Condition: New
Quantity: 1 available
Add to basketSold by Grand Eagle Retail, Bensenville, IL, U.S.A.
AbeBooks Seller since 12 October 2005
Condition: New
Quantity: 1 available
Add to basketPaperback. 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.
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