Practical Weak Supervision : Doing More with Less Data (Record no. 45809)
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000 -LEADER | |
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fixed length control field | 01577 a2200193 4500 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9789355420435 |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 006.31 TOK |
100 ## - MAIN ENTRY--PERSONAL NAME | |
Personal name | Tok, Wee Hyong |
245 ## - TITLE STATEMENT | |
Title | Practical Weak Supervision : Doing More with Less Data |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
Name of publisher, distributor, etc | Shroff/O'Reilly |
Place of publication, distribution, etc | USA |
Date of publication, distribution, etc | 2022 |
300 ## - PHYSICAL DESCRIPTION | |
Extent | 169 |
520 ## - SUMMARY, ETC. | |
Summary, etc | Most data scientists and engineers today rely on quality labeled data to train their machine learning models. But building training sets manually is time-consuming and expensive, leaving many companies with unfinished ML projects. There's a more practical approach. In this book, Amit Bahree, Senja Filipi, and Wee Hyong Tok from Microsoft show you how to create products using weakly supervised learning models. You'll learn how to build natural language processing and computer vision projects using weakly labeled datasets from Snorkel, a spin-off from the Stanford AI Lab. Because so many companies pursue ML projects that never go beyond their labs, this book also provides a guide on how to ship the deep learning models you build. Get a practical overview of weak supervision Dive into data programming with help from Snorkel Perform text classification using Snorkel's weakly labeled dataset Use Snorkel's labeled indoor-outdoor dataset for computer vision tasks Scale up weak supervision using scaling strategies and underlying technologies |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Supervised learning (Machine learning) |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Natural language processing (Computer science) |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Computer vision |
700 ## - ADDED ENTRY--PERSONAL NAME | |
Personal name | Bahree, Amit |
700 ## - ADDED ENTRY--PERSONAL NAME | |
Personal name | Filipi, Senja |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | Book |
Source of classification or shelving scheme | Dewey Decimal Classification |
No items available.