Introduction to algorithms for data mining and machine learning /
General Material Designation
[Book]
First Statement of Responsibility
Xin-She Yang.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
San Diego, CA, United States :
Name of Publisher, Distributor, etc.
Academic Press, an imprint of Elsevier,
Date of Publication, Distribution, etc.
[2019]
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (viii, 173 pages) :
Other Physical Details
illustrations
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references (pages 163-170) and index.
CONTENTS NOTE
Text of Note
Introduction to optimization -- Mathematical foundations -- Optimization algorithms -- Data fitting and regression -- Logistic regression, PCA, LDA, and ICA -- Data mining techniques -- Support vector machine and regression -- Neural networks and deep learning.
0
SUMMARY OR ABSTRACT
Text of Note
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.
ACQUISITION INFORMATION NOTE
Source for Acquisition/Subscription Address
Ingram Content Group
Stock Number
9780128172179
OTHER EDITION IN ANOTHER MEDIUM
Title
Introduction to algorithms for data mining and machine learning.