Machine Learning
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Machine Learning

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Description

This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.

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Product details

  • Paperback | 352 pages
  • 149.86 x 236.22 x 20.32mm | 544.31g
  • McGraw-Hill Education - Europe
  • McGraw Hill Higher Education
  • London, United States
  • English
  • International edition
  • 0071154671
  • 9780071154673
  • 123,081

Table of contents

Chapter 1. Introduction Chapter 2. Concept Learning and the General-to-Specific Ordering Chapter 3. Decision Tree Learning Chapter 4. Artificial Neural Networks Chapter 5. Evaluating Hypotheses Chapter 6. Bayesian Learning Chapter 7. Computational Learning Theory Chapter 8. Instance-Based Learning Chapter 9. Inductive Logic Programming Chapter 10. Analytical Learning Chapter 11. Combining Inductive and Analytical Learning Chapter 12. Reinforcement Learning.

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