Mathematical Foundations for Data Analysis

Name: Mathematical Foundations for Data Analysis
Brand: Springer Nature Switzerland AG
SKU: 9783030623401
Price: 308.26 RON
Availability: InStock

Autor: Jeff M. Phillips

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Legare: Copertă tare

Editura: Springer Nature Switzerland AG

Disponibilitate: În depozitul extern

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308.26 lei

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

Informații despre carte

Autor

Jeff M. Phillips

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2021

Pagini

287

EAN

9783030623401

ISBN

3030623408

Enbook ID

35425744

Editura

Springer Nature Switzerland AG

Greutate

666

Dimensiuni

242 x 159 x 27

Descriere completă

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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