Machine learning for civil & environmental engineers : a practical approach to data-driven analysis, explainability, and causality / M.Z. Naser
Material type:
TextPublisher: Hoboken, New Jersey : John Wiley & Sons, [2023]Description: xix, 588 pages : illustrationsContent type: - text
- unmediated
- volume
- 9781119897606
- Machine learning for civil and environmental engineers
- 006.31
| Item type | Current library | Collection | Call number | Copy number | Status | Barcode | |
|---|---|---|---|---|---|---|---|
Book
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Lagro Branch Reference Section | Reference | R 006.31 N247m 2023 (Browse shelf(Opens below)) | c. 2 | Room use only | 57745QC | |
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Book
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Main Library Reference Section | Reference | R 006.31 N247m 2023 (Browse shelf(Opens below)) | c. 1 | Room use only | 57744QC |
Browsing Main Library shelves, Shelving location: Reference Section, Collection: Reference Close shelf browser (Hides shelf browser)
| R 005.824 M265c 2024 Cryptography : algorithms, protocols, and standards for computer security | R 006.3 Ar791 2024 Artificial intelligence and knowledge processing : improved decision-making and prediction | R 006.3 T693c 2023 Contemporary artificial intelligence | R 006.31 N247m 2023 Machine learning for civil & environmental engineers : a practical approach to data-driven analysis, explainability, and causality | R 006.5 F771 2020 Foundations in sound design for interactive media : a multidisciplinary approach | R 006.6 K23p 2005 Paint Shop Pro 9 for dummies | R 006.6 M363f 2016 Fundamentals of computer graphics |
Includes bibliographical references and index.
Teaching methods for this textbook
Introduction to machine learning
Data and statistics
Machine learning algorithms
Performance fitness indicators and error metrics
Coding-free and coding-based approaches to machine learning
Explainability and interpretability
Causal discovery and casual inference
Final thoughts and future directions
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