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Library,Documentation and Information Science Division

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Pattern recognition and machine learning / Christopher M. Bishop.

By: Material type: TextTextSeries: Information science and statisticsPublication details: New Delhi : Springer, 2013.Description: xx, 738 p. : illustrations ; 24 cmISBN:
  • 9788132209065
Subject(s): DDC classification:
  • 006.4 23 B622
Contents:
1. Introduction-- 2. Probability distributions-- 3. Linear models for regression-- 4. Linear models for classification-- 5. Neural networks-- 6. Kernel methods-- 7. Sparse kernel machines-- 8. Graphical models-- 9. Mixture models and EM-- 10. Approximate inference-- 11. Sampling methods-- 12. Continuous latent variables-- 13. Sequential data-- 14. Combining models-- Appendices-- References-- Index.
Summary: The field of pattern recognition has undergone substantial development over the years. This book reflects these developments while providing a grounding in the basic concepts of pattern recognition and machine learning. It is aimed at advanced undergraduates or first year PhD students, as well as researchers and practitioners
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 006.4 B622 (Browse shelf(Opens below)) Available PC3431
Total holds: 0

Includes bibliographical references and index.

1. Introduction--
2. Probability distributions--
3. Linear models for regression--
4. Linear models for classification--
5. Neural networks--
6. Kernel methods--
7. Sparse kernel machines--
8. Graphical models--
9. Mixture models and EM--
10. Approximate inference--
11. Sampling methods--
12. Continuous latent variables--
13. Sequential data--
14. Combining models--
Appendices--
References--
Index.

The field of pattern recognition has undergone substantial development over the years. This book reflects these developments while providing a grounding in the basic concepts of pattern recognition and machine learning. It is aimed at advanced undergraduates or first year PhD students, as well as researchers and practitioners

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