| 000 | 00000nam u2200205 a 4500 | |
| 001 | 000046037774 | |
| 005 | 20200723150324 | |
| 008 | 200723s2020 maua b 001 0 eng d | |
| 010 | ▼a 2019027152 | |
| 020 | ▼a 9780262538701 (paperback) | |
| 020 | ▼z 9780262358019 (ebook) | |
| 035 | ▼a (KERIS)REF000019151366 | |
| 040 | ▼a DLC ▼b eng ▼e rda ▼c DLC ▼d 211009 | |
| 050 | 0 0 | ▼a Q325.5 ▼b .G68 2020 |
| 082 | 0 0 | ▼a 006.3/1 ▼2 23 |
| 084 | ▼a 006.31 ▼2 DDCK | |
| 090 | ▼a 006.31 ▼b G698p | |
| 100 | 1 | ▼a Goulet, James-A. |
| 245 | 1 0 | ▼a Probabilistic machine learning for civil engineers / ▼c James-A. Goulet. |
| 260 | ▼a Cambridge, Massachusetts : ▼b The MIT Press, ▼c 2020. | |
| 300 | ▼a xxviii, 269 p. : ▼b ill. (some col.) ; ▼c 26 cm. | |
| 504 | ▼a Includes bibliographical references and index. | |
| 520 | ▼a "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"-- ▼c Provided by publisher. | |
| 650 | 0 | ▼a Machine learning. |
| 650 | 0 | ▼a Probabilities. |
| 945 | ▼a KLPA |
Holdings Information
| No. | Location | Call Number | Accession No. | Availability | Due Date | Make a Reservation | Service |
|---|---|---|---|---|---|---|---|
| No. 1 | Location Science & Engineering Library/Sci-Info(Stacks2)/ | Call Number 006.31 G698p | Accession No. 121253866 | Availability Available | Due Date | Make a Reservation | Service |
