Introducing Active Machine Learning

Machine learning models require large, labeled datasets, which can be expensive and time-consuming to obtain. Active machine learning (active ML) minimizes the labeling effort needed by intelligently choosing which data points a human should label. In this book, you will gain the necessary knowledge to understand active learning, including its mechanisms and applications. With these fundamentals, the subsequent chapters will equip you with concrete skills to implement active learning techniques on your own.

By the end of this book, you will have practical experience with state-of-the-art strategies to minimize labeling costs and maximize model performance. You will be able to apply active learning to enhance the efficiency and adaptability of your models across different application areas, such as vision and language.

To begin with, this chapter provides an introduction to active ML and explains how it can improve model accuracy using fewer...