A first course in machine learning / Simon Rogers, Mark Girolami.
Material type:
TextPublisher: Boca Raton : CRC Press, 2017Description: xxviii, 397: pages ill. ; 25 cmISBN: 978-1-4987-3848-4Subject(s): Machine learning | BUSINESS & ECONOMICS / Statistics | COMPUTERS / General | COMPUTERS / Database Management / Data MiningDDC classification: 006.31, ROG LOC classification: Q325.5 | .R64 2012Other classification: BUS061000 | COM000000 | COM021030
Contents:
Linear Modeling: A least Squares Approach (Page-3), Linear Modeling: A Maximum Likelihood Approach (Page-41), The Bayesian Approach to Machine Learning (Page-95), Bayesian Inference (Page-137), Classification (Page-167), Clustering (Page-205), Principal Components Analysis and Latent Variable Models (Page-235), Gaussian Process (Page-275), Markov Chain Monte Carlo Sampling (Page-315), Advanced Mixture Modeling (Page-351).
| Item type | Current location | Home library | Shelving location | Call number | Status | Notes | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|---|---|
Reference
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Military College of Signals (MCS) | Military College of Signals (MCS) | Reference | 006.31,ROG (Browse shelf) | Not for loan | Almirah No.18, Shelf No.5 | MCS38155 |
Total holds: 0
Linear Modeling: A least Squares Approach (Page-3), Linear Modeling: A Maximum Likelihood Approach (Page-41), The Bayesian Approach to Machine Learning (Page-95), Bayesian Inference (Page-137), Classification (Page-167), Clustering (Page-205), Principal Components Analysis and Latent Variable Models (Page-235), Gaussian Process (Page-275), Markov Chain Monte Carlo Sampling (Page-315), Advanced Mixture Modeling (Page-351).
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