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£86.90
MIT Press Probabilistic Machine Learning: An Introduction
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Description
Key Features
Comprehensive coverage of probabilistic modeling and Bayesian decision theory to provide a unified view of machine learning.
Includes essential mathematical foundations such as linear algebra and optimization to prepare readers for advanced study.
Explains fundamental supervised learning methods including linear regression, logistic regression, and deep neural networks.
Covers advanced machine learning topics such as transfer learning and unsupervised learning for deeper technical expertise.
Provides up-to-date insights into deep learning methodologies within a probabilistic framework.
Published by MIT Press as part of the Adaptive Computation and Machine Learning series for academic rigor.
Product Specifications
- Brand
- MIT Press
- Colour
- Navy
- Format
- hardcover
- ASIN
- 0262046822
- Domain
- Amazon UK
- Release Date
- 01 February 2022
- Listed Since
- 13 May 2021
Barcode
No barcode data available
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