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Model-Based Machine Learning

Resource type
Author/contributor
Title
Model-Based Machine Learning
Abstract
This book is unusual for a machine learning text book in that the authors do not review dozens of different algorithms. Instead they introduce all of the key ideas through a series of case studies involving real-world applications. Case studies play a central role because it is only in the context of applications that it makes sense to discuss modelling assumptions. Each chapter therefore introduces one case study which is drawn from a real-world application that has been solved using a model-based approach.
Publisher
Taylor & Francis Incorporated
Date
2019-06
# of Pages
400
Language
en
ISBN
978-1-4987-5681-5
Library Catalog
Google Books
Extra
ZSCC: NoCitationData[s1] Google-Books-ID: 84KRtgEACAAJ
Citation
Winn, J. M. (2019). Model-Based Machine Learning. Taylor & Francis Incorporated.
PROBABILITY & STATISTICS
Methodology
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