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Mathematical Foundations for Data Analysis

Language EnglishEnglish
Book Paperback
Book Mathematical Foundations for Data Analysis Jeff M. Phillips
Libristo code: 38823409
Publishers Springer Nature Switzerland AG, March 2022
This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of... Full description
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23 491 Ft
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This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparation for students planning to take rigorous Machine Learning and Data Mining courses. It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and principal component analysis. It also surveys basic techniques in supervised (regression and classification) and unsupervised learning (dimensionality reduction and clustering) through an accessible, simplified presentation. Students are recommended to have some background in calculus, probability, and linear algebra. Some familiarity with programming and algorithms is useful to understand advanced topics on computational techniques.

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About the book

Full name Mathematical Foundations for Data Analysis
Language English
Binding Book - Paperback
Date of issue 2022
Number of pages 287
EAN 9783030623432
Libristo code 38823409
Weight 474
Dimensions 155 x 235 x 17
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