Pattern recognition and machine learning Christopher M Bishop
Material type:
TextPublication details: New York : Springer, ©2006.Description: 738 pagesISBN: - 9781493938438
- 006.4 BIS
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IIITDM Kurnool Reference | Reference | 006.4 BIS (Browse shelf(Opens below)) | Not For Loan | 0004024 | |
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| 006.3843 LAL Quantum computing : a beginner's introduction | 006.3843 LAL Quantum computing : a beginner's introduction | 006.4 BIS Neural networks for pattern recognition | 006.4 BIS Pattern recognition and machine learning | 006.6 EHS Data acquisition using labVIEW : | 006.6 EHS Data acquisition using labVIEW : | 006.6 EHS Data acquisition using labVIEW : |
Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- . Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models
Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
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