Practicing Trustworthy Machine Learning (Record no. 45806)
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000 -LEADER | |
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fixed length control field | 01230 a2200169 4500 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9789355422194 |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 006.31 PRU |
100 ## - MAIN ENTRY--PERSONAL NAME | |
Personal name | Pruksachatkun, Yada |
245 ## - TITLE STATEMENT | |
Title | Practicing Trustworthy Machine Learning |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
Name of publisher, distributor, etc | Shroff Publishers & Distributors Pvt. Ltd. |
Place of publication, distribution, etc | Mumbai |
Date of publication, distribution, etc | 2023 |
300 ## - PHYSICAL DESCRIPTION | |
Extent | 274 |
520 ## - SUMMARY, ETC. | |
Summary, etc | With the increasing use of AI in high-stakes domains such as medicine, law, and defense, organizations spend a lot of time and money to make ML models trustworthy. Many books on the subject offer deep dives into theories and concepts. This guide provides a practical starting point to help development teams produce models that are secure, more robust, less biased, and more explainable.<br/><br/>Authors Yada Pruksachatkun, Matthew McAteer, and Subhabrata Majumdar translate best practices in the academic literature for curating datasets and building models into a blueprint for building industry-grade trusted ML systems. With this book, engineers and data scientists will gain a much-needed foundation for releasing trustworthy ML applications into a noisy, messy, and often hostile world. |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Machine Learning |
700 ## - ADDED ENTRY--PERSONAL NAME | |
Personal name | Mcateer,Matthew |
700 ## - ADDED ENTRY--PERSONAL NAME | |
Personal name | Majumdar, Subhabrata |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | Book |
Source of classification or shelving scheme | Dewey Decimal Classification |
No items available.