Probabilistic Machine Learning : An Introduction
Language: English Publication details: Cambridge MIT Press 2022Description: 826ISBN: 9780262046824Subject(s): Machine learning | Probabilities | Computer ScienceSummary: This book provides a detailed and up-to-date coverage of machine learning. It is unique in that it unifies approaches based on deep learning with approaches based on probabilistic modeling and inference. It provides mathematical background (e.g. linear algebra, optimization), basic topics (e.g., linear and logistic regression, deep neural networks), as well as more advanced topics (e.g., Gaussian processes). It provides a perfect introduction for people who want to understand cutting edge work in top machine learning conferences such as NeurIPS, ICML and ICLR"-- Provided by publisher.
BOOKS
List(s) this item appears in:
New Arrivals (21 April 2022)
| Current library | Home library | Call number | Materials specified | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
| IMSc Library | IMSc Library | 681.3 MUR (Browse shelf (Opens below)) | Available | 76179 |
This book provides a detailed and up-to-date coverage of machine learning. It is unique in that it unifies approaches based on deep learning with approaches based on probabilistic modeling and inference. It provides mathematical background (e.g. linear algebra, optimization), basic topics (e.g., linear and logistic regression, deep neural networks), as well as more advanced topics (e.g., Gaussian processes). It provides a perfect introduction for people who want to understand cutting edge work in top machine learning conferences such as NeurIPS, ICML and ICLR"-- Provided by publisher.
There are no comments on this title.