Mathematical Foundations for Data Analysis

Name: Mathematical Foundations for Data Analysis
Brand: Springer Nature Switzerland AG
SKU: 9783030623401
Price: 1342 CZK
Availability: InStock

Autor: Jeff M. Phillips

Jazyk:

Vazba: Pevná

Vydavatel: Springer Nature Switzerland AG

Dostupnost: Skladem u dodavatele

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This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of...

Informace o knize

Autor

Jeff M. Phillips

Jazyk

Angličtina

Vazba

Kniha - Pevná

Vydáno

2021

Stránek

287

EAN

9783030623401

ISBN

3030623408

Enbook ID

35425744

Vydavatel

Springer Nature Switzerland AG

Hmotnost

666

Rozměry

242 x 159 x 27

Kompletní popis

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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Mathematical Foundations for Data Analysis

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Mathematical Foundations for Data Analysis

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