Introduction to Algorithms for Data Mining and Machine Learning (ePub)

Name: Introduction to Algorithms for Data Mining and Machine Learning
Brand: Elsevier Science & Techn.
SKU: 111699823
Price: 65.95 EUR
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(Sprache: Englisch)

Autor: Xin-She Yang

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Introduction to Algorithms for Data Mining and Machine Learning, Xin-She Yang

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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...

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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.

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

Autoren-Porträt von Xin-She Yang

Xin-She Yang obtained his DPhil in Applied Mathematics from the University of Oxford. He then worked at Cambridge University and National Physical Laboratory (UK) as a Senior Research Scientist. He is currently a Reader at Middlesex University London, Adjunct Professor at Reykjavik University (Iceland) and Guest Professor at Xi'an Polytechnic University (China). He is an elected Bye-Fellow at Downing College, Cambridge University. He is also the IEEE CIS Chair for the Task Force on Business Intelligence and Knowledge Management, and the Editor-in-Chief of International Journal of Mathematical Modelling and Numerical Optimisation (IJMMNO).

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Bibliographische Angaben

Autor: Xin-She Yang
2019, 188 Seiten, Englisch
Verlag: Elsevier Science & Techn.
ISBN-10: 0128172177
ISBN-13: 9780128172179
Erscheinungsdatum: 17.06.2019

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Dateiformat: ePub
Größe: 6.93 MB
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