Machine Learning

Klappentext:

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.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.

Inhaltsverzeichnis:

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.

Themen:

• Maschinelles Lernen

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• Data Mining
• Künstliche Intelligenz
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• Neuronale Netze
• Dialogsysteme
• Evolutionäre Algorithmen
• Gauß, Carl Fr.
• Mustererkennung
• Algorithmen