Introduction to Machine Learning
eBook - PDF

Introduction to Machine Learning

  1. 305 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Introduction to Machine Learning

About this book

A textbook suitable for undergraduate courses in machine learningand related topics, this book provides a broad survey of the field.Generous exercises and examples give students a firm grasp of theconcepts and techniques of this rapidly developing, challenging subject. Introduction to Machine Learning synthesizes and clarifiesthe work of leading researchers, much of which is otherwise availableonly in undigested technical reports, journals, and conference proceedings.Beginning with an overview suitable for undergraduate readers, Kodratoffestablishes a theoretical basis for machine learning and describesits technical concepts and major application areas. Relevant logicprogramming examples are given in Prolog. Introduction to Machine Learning is an accessible and originalintroduction to a significant research area.

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Table of contents

  1. Front Cover
  2. Introduction to Machine Learning
  3. Copyright Page
  4. Table of Contents
  5. Foreword and Acknowledgements
  6. Chapter 1. Why Machine Learning and Artificial Intelligence? The Contribution of Artificial Intelligence to Learning Techniques
  7. Chapter 2. Theoretical Foundations for Machine Learning
  8. Chapter 3. Representation of Complex Knowledge by Clauses
  9. Chapter 4. Representation of Knowledge About Actions and the Addition of New Rules to a Knowledge Base
  10. Chapter 5. Learning by Doing
  11. Chapter 6. A Formal Presentation of Version Spaces
  12. Chapter 7. Explanation-Based Learning
  13. Chapter 8. Learning by Similarity Detection The Empirical Approach
  14. Chapter 9. Learning by Similarity Detection The 'Rational' Approach
  15. Chapter 10. Automatic Construction of Taxonomies Techniques for Clustering
  16. Chapter 11. Debugging and Understanding in Depth The Learning of Micro-Worlds
  17. Chapter 12. Learning by Analogy
  18. Appendix 1: Equivalence Between Theorems and Clauses
  19. Appendix 2: Synthesis of Predicates
  20. Appendix 3: Machine Learning in Context
  21. Bibliography
  22. Index

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Yes, you can access Introduction to Machine Learning by Yves Kodratoff in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.