Probabilistic machine learning: (Record no. 7426)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01992nam a2200205 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250105120218.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250105b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780262048439 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31015192 |
| Item number | MUR |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Murphy, Kevin P |
| 245 ## - TITLE STATEMENT | |
| Title | Probabilistic machine learning: |
| Remainder of title | advanced topics |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher, distributor, etc. | The MIT press |
| Place of publication, distribution, etc. | Cambridge |
| Date of publication, distribution, etc. | 2023 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xxxi, 1319 p. |
| 365 ## - TRADE PRICE | |
| Price type code | USD |
| Price amount | 150.00 |
| 490 ## - SERIES STATEMENT | |
| Series statement | Adaptive Computation and Machine Learning |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty.<br/><br/>An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in machine learning, including deep generative modeling, graphical models, Bayesian inference, reinforcement learning, and causality. This volume puts deep learning into a larger statistical context and unifies approaches based on deep learning with ones based on probabilistic modeling and inference. With contributions from top scientists and domain experts from places such as Google, DeepMind, Amazon, Purdue University, NYU, and the University of Washington, this rigorous book is essential to understanding the vital issues in machine learning.<br/><br/><br/>• Covers generation of high dimensional outputs, such as images, text, and graphs<br/>• Discusses methods for discovering insights about data, based on latent variable models<br/>• Considers training and testing under different distributions<br/>• Explores how to use probabilistic models and inference for causal inference and decision making<br/>• Features online Python code accompaniment<br/>(https://mitpress.mit.edu/9780262048439/probabilistic-machine-learning/) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Probabilities |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Book |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Bill No | Bill Date | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Total Checkouts | Full call number | Accession Number | Date last seen | Copy number | Cost, replacement price | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | IT & Decisions Sciences | 670/24-25 | 21-12-2024 | Indian Institute of Management LRC | Indian Institute of Management LRC | General Stacks | 01/09/2025 | T V Enterprises | 8502.00 | 006.31015192 MUR | 007056 | 01/09/2025 | 1 | 13080.00 | 01/09/2025 | Book |