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Machine Learning / Tom M Mitchell

By: Contributor(s): Material type: TextTextPublisher number: :Donated from Prof Madan GopalPublication details: New York : McGraw-Hill, ©1997.Description: xvii, 414 pages : illustrations ; 25 cmISBN:
  • 9780071154673
Subject(s): DDC classification:
  • 006.31 MIT
Contents:
1. Introduction -- 2. Concept Learning and the General-to-Specific Ordering -- 3. Decision Tree Learning -- 4. Artificial Neural Networks -- 5. Evaluating Hypotheses -- 6. Bayesian Learning -- 7. Computational Learning Theory -- 8. Instance-Based Learning -- 9. Genetic Algorithms -- 10. Learning Sets of Rules -- 11. Analytical Learning -- 12. Combining Inductive and Analytical Learning -- 13. Reinforcement Learning.
Summary: Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data
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Holdings
Item type Current library Call number Status Barcode
Mathematics Departmental Library Mathematics Departmental Library Mathematics Departmental Library 006.31 MIT (Browse shelf(Opens below)) Available M376
Total holds: 0

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

Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data

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