
Автор: Wee Hyong Tok, Amit Bahree, Senja Filipi
Издательство: O’Reilly Media, Inc.
Год: 2021
Страниц: 200
Язык: английский
Формат: epub
Размер: 10.2 MB
Build products using Deep Learning, weakly supervised learning, and natural language processing without collecting millions of training records. This practical book explains how and provides a how-to guide for actually shipping deep learning models–since most of these projects never leave the lab. Deep networks have enabled new applications using unstructured data to proliferate, but much of the work means collecting millions of records as well as labeled datasets. Author Russell Jurney from Data Syndrome helps machine-learning engineers, software engineers, deep learning engineers, and data scientists learn practical applications using several weakly supervised learning methods.