Human-in-the-Loop Machine Learning
Author | : Robert Munro |
Publisher | : Simon and Schuster |
Total Pages | : 422 |
Release | : 2021-07-20 |
ISBN-10 | : 9781617296741 |
ISBN-13 | : 1617296740 |
Rating | : 4/5 (740 Downloads) |
Download or read book Human-in-the-Loop Machine Learning written by Robert Munro and published by Simon and Schuster. This book was released on 2021-07-20 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-loop machine learning lays out methods for humans and machines to work together effectively. You'll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You'll learn to dreate training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows.