AI & Computer Science · AI Books
Human-in-the-Loop Machine Learning: Active Learning and Annotation for Human-Centered AI (Robert Monarch)
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Robert Monarch explains how human judgment and machine learning can work together to build better models.
Active learning uses uncertainty and diversity sampling to select examples that most need human feedback.
The book examines how to recruit annotators, write instructions, and measure agreement and annotation quality.
It connects reliable training and evaluation data with transfer learning and other ways to improve labeling workflows.
Annotation interfaces and human-computer interaction bring these methods together in practical machine learning products.
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