
Practical Weak Supervision
Doing More with Less Data
O'Reilly (Publisher)
Published on 31. October 2021
Book
Paperback/Softback
200 pages
978-1-4920-7706-0 (ISBN)
Description
Most data scientists and engineers today rely on quality labeled data to train machine learning models. But building a training set manually is time-consuming and expensive, leaving many companies with unfinished ML projects. There's a more practical approach. In this book, Wee Hyong Tok, Amit Bahree, and Senja Filipi 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 have pursued 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 up to speed on the field of weak supervision, including ways to use it as part of the data science process
Use Snorkel AI for weak supervision and data programming
Get code examples for using Snorkel to label text and image datasets
Use a weakly labeled dataset for text and image classification
Learn practical considerations for using Snorkel with large datasets and using Spark clusters to scale labeling
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 have pursued 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 up to speed on the field of weak supervision, including ways to use it as part of the data science process
Use Snorkel AI for weak supervision and data programming
Get code examples for using Snorkel to label text and image datasets
Use a weakly labeled dataset for text and image classification
Learn practical considerations for using Snorkel with large datasets and using Spark clusters to scale labeling
More details
Language
English
Place of publication
Sebastopol
United States
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 231 mm
Width: 176 mm
Thickness: 12 mm
Weight
346 gr
ISBN-13
978-1-4920-7706-0 (9781492077060)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Wee Hyong Tok | Amit Bahree | Senja Filipi
Practical Weak Supervision
E-Book
09/2021
O'Reilly
€50.49
Available for download

Wee Hyong Tok | Amit Bahree | Senja Filipi
Practical Weak Supervision
E-Book
09/2021
O'Reilly
€50.49
Available for download
Persons
Wee Hyong is a product and AI leader with a background in product management, machine learning/deep learning, research, and working on complex technical engagements with customers. Over the years, he has demonstrated that the early thought-leadership whitepapers he wrote on tech trends have become reality, and are deeply integrated into many products. Wee Hyong has worn many hats in his career-developer, program/product manager, data scientist, researcher, and strategist, and his range of experience has given him unique superpowers to lead and define the strategy for high-performing data and AI innovation teams.