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Probabilistic machine learning for civil engineers.
- Publication Year :
- 2020
-
Abstract
- Summary: "The book introduces probabilistic machine learning concepts to civil engineering students and professionals, who typically do not have the background necessary to understand the subject from a purely computer science perspective. It presents key approaches among the three sub-fields of machine learning: supervised, unsupervised, and reinforcement learning. The methods are demonstrated through step-by-step examples and copius illustrations in order to simplify abstract concepts. The book will prepare readers to access the vast body of literature from the field of machine learning"-- Provided by publisher.
- Subjects :
- Machine learning
Probabilities
Machine Learning--Civil engineers
Subjects
Details
- Language :
- English
- ISBN :
- 9780262538701 (pbk.)
- ISBNs :
- 9780262538701
- Database :
- Jio Institute Digital Library Catalog
- Journal :
- Probabilistic machine learning for civil engineers / James-A. Goulet.
- Notes :
- Includes bibliographical references (pages [259]-266) and index.
- Publication Type :
- Book
- Accession number :
- jlc.oai.folio.org.fs00001072.22855eca.c276.4853.93c3.eb8689978f2d
- Document Type :
- Bibliographies; Non-fiction