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Introduction to machine learning Ethem Alpaydın.

By: Material type: TextTextPublication details: New Delhi : Prentice-Hall of India, c2004. [reprinted 2006]Description: xxx, 415 p. : ill. , figs.; 24 cmISBN:
  • 0262012111
Subject(s): DDC classification:
  • 006.31/ A456i 22
LOC classification:
  • Q325.5 .A473 2004
Contents:
1. Introduction -- 2. Supervised learning -- 3. Bayesian decision theory -- 4. Parametric methods -- 5. Multivariate methods -- 6. Dimensionality reduction -- 7. Clustering -- 8. Nonparametric methods -- 9. Decision trees -- 10. Linear discrimination -- 11. Multilayer perceptrons -- 12. Local models -- 13. Hidden Markov models -- 14. Assessing and comparing classification algorithms -- 15. Combining multiple learners -- 16. Reinforcement learning -- A. Probability.
Review: "This book can be used by advanced undergraduates and graduate students who have completed courses in computer programming, probability, calculus, and linear algebra. It will also be of interest to engineers in the field who are concerned with the application of machine learning methods."--BOOK JACKET.
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Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode Item holds
Book Book Daffodil International University Library General Stacks Non-fiction 006.31/ A456i (Browse shelf(Opens below)) 1 Available 010358
Total holds: 0

Includes bibliographical references and index.

1. Introduction -- 2. Supervised learning -- 3. Bayesian decision theory -- 4. Parametric methods -- 5. Multivariate methods -- 6. Dimensionality reduction -- 7. Clustering -- 8. Nonparametric methods -- 9. Decision trees -- 10. Linear discrimination -- 11. Multilayer perceptrons -- 12. Local models -- 13. Hidden Markov models -- 14. Assessing and comparing classification algorithms -- 15. Combining multiple learners -- 16. Reinforcement learning -- A. Probability.

"This book can be used by advanced undergraduates and graduate students who have completed courses in computer programming, probability, calculus, and linear algebra. It will also be of interest to engineers in the field who are concerned with the application of machine learning methods."--BOOK JACKET.

CSE, CIS, CS

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