Introduction to Algorithms for Data Mining and Machine Learning - Edition 1 - By Xin-She Yang Elsevier Educate

Introduction to Algorithms for Data Mining and Machine Learning

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Introduction to Algorithms for Data Mining and Machine Learning,

Edition 1

By Xin-She Yang

Publication Date: 19 Jun 2019

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Introduction to Algorithms for Data Mining and Machine Learning introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematical approach, well selected examples, and practical software recommendations help readers develop confidence in their data modeling skills so they can process and interpret data for classification, clustering, curve-fitting and predictions. Masterfully balancing theory and practice, it is especially useful for those who need relevant, well explained, but not rigorous (proofs based) background theory and clear guidelines for working with big data.

Key Features

Presents an informal, theorem-free approach with concise, compact coverage of all fundamental topics
Includes worked examples that help users increase confidence in their understanding of key algorithms, thus encouraging self-study
Provides algorithms and techniques that can be implemented in any programming language, with each chapter including notes about relevant software packages

About the author

By Xin-She Yang, School of Science and Technology, Middlesex University, UK

ISBN: 9780128172162

Page Count: 188

Retail Price (USD) :

Anzai, Pattern Recognition and Machine Learning, Dec 2012, 9780120588305, 407pp, $72.95
Gori, Machine Learning: A Constraint-Based Approach, Nov 2017, 9780081006597, 580pp, $99.95
Han, Kamber and Pei, Data Mining: Concepts and Techniques, 3e, Jun 2011, 9780123814791, 744pp, $74.95

Undergraduates and graduates in computer science, management science, economics, and engineering will use the book in courses on data mining, machine learning, and optimization

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