Overview
- Provides comprehensive coverage of both learning algorithms: supervised and unsupervised learning
- Outlines the computation paradigm for solving classification, regression, and clustering
- Features essential techniques for building the a new generation of machine learning
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Table of contents (16 chapters)
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Front Matter
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Foundation
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Front Matter
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Supervised Learning
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Front Matter
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Unsupervised Learning
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Front Matter
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Advanced Topics
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Front Matter
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Keywords
About this book
This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists of four parts: foundation, supervised learning, unsupervised learning, and advanced learning. The first part provides the fundamental materials, background, and simple machine learning algorithms, as the preparation for studying machine learning algorithms. The second and the third parts provide understanding of the supervised learning algorithms and the unsupervised learning algorithms as the core parts. The last part provides advanced machine learning algorithms: ensemble learning, semi-supervised learning, temporal learning, and reinforced learning.
- Provides comprehensive coverage of both learning algorithms: supervised and unsupervised learning;
- Outlines the computation paradigm for solving classification, regression, and clustering;
- Features essential techniques for building the a new generation of machine learning.
Authors and Affiliations
About the author
Taeho Jo is the president and the founder of the company, Alpha Lab AI which makes business concerned with Artificial Intelligence. He received his Bachelor, Master, and PhD degrees from Korea University in 1994, from Pohang University in 1997, and from University of Ottawa, 2006, respectively. He has published more than 180 research papers, primarily in text mining, machine learning, neural networks, and information retrieval. He previously published the book “Text Mining: Concept, Implementation, and Big Data Challenge” (Springer 2018).
Bibliographic Information
Book Title: Machine Learning Foundations
Book Subtitle: Supervised, Unsupervised, and Advanced Learning
Authors: Taeho Jo
DOI: https://doi.org/10.1007/978-3-030-65900-4
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-65899-1Published: 13 February 2021
Softcover ISBN: 978-3-030-65902-8Published: 13 February 2022
eBook ISBN: 978-3-030-65900-4Published: 12 February 2021
Edition Number: 1
Number of Pages: XX, 391
Number of Illustrations: 264 b/w illustrations, 13 illustrations in colour
Topics: Communications Engineering, Networks, Computational Intelligence, Data Mining and Knowledge Discovery, Information Storage and Retrieval, Big Data/Analytics