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© 2021

Machine Learning Foundations

Supervised, Unsupervised, and Advanced Learning

Book
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Table of contents

  1. Front Matter
    Pages i-xx
  2. Foundation

    1. Front Matter
      Pages 1-1
    2. Taeho Jo
      Pages 3-22
    3. Taeho Jo
      Pages 23-45
    4. Taeho Jo
      Pages 47-68
    5. Taeho Jo
      Pages 69-90
  3. Supervised Learning

    1. Front Matter
      Pages 91-91
    2. Taeho Jo
      Pages 93-115
    3. Taeho Jo
      Pages 117-139
    4. Taeho Jo
      Pages 141-165
    5. Taeho Jo
      Pages 167-188
  4. Unsupervised Learning

    1. Front Matter
      Pages 189-189
    2. Taeho Jo
      Pages 191-215
    3. Taeho Jo
      Pages 217-240
    4. Taeho Jo
      Pages 241-260
    5. Taeho Jo
      Pages 261-282
  5. Advanced Topics

    1. Front Matter
      Pages 283-283
    2. Taeho Jo
      Pages 285-307
    3. Taeho Jo
      Pages 309-334
    4. Taeho Jo
      Pages 335-358

About this book

Introduction

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.

Keywords

Machine Learning Supervised Learning K nearest Neighbor Naïve Bayes Neural Networks Support Vector Machine Unsupervised Learning K Means Algorithm EM Algorithm Fuzzy Clustering Hierarchical Clustering

Authors and affiliations

  1. 1.Hongik UniversityGarosuro CheongjuKorea (Republic of)

About the authors

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