Human in the Loop Machine Learning

توضیحات

This book explores the concept of human-in-the-loop (HITL) machine learning, where human expertise is integrated into the training, evaluation, and refinement of machine learning models. It covers techniques for active learning, data labeling, model debugging, and interactive AI systems. Through practical examples and case studies, readers learn how to leverage human input to improve accuracy, reduce errors, and handle complex or ambiguous data. The text also discusses workflow design, scalability challenges, and the ethical implications of human-AI collaboration. By the end, readers gain the skills to implement effective human-in-the-loop strategies for building robust, accurate, and trustworthy machine learning systems.