Active Learning is a machine learning approach where an AI system identifies the most useful or uncertain data and requests human input to improve its learning process. Instead of labeling large datasets manually, organizations can focus on the data that provides the greatest value.
Active Learning reduces data-labeling effort, improves model accuracy, and accelerates AI development. It is used in computer vision, healthcare, manufacturing, autonomous systems, security, and natural language processing. Related technologies include machine learning, deep learning, human-in-the-loop AI, and data annotation. Related terms include Supervised Learning, Semi-Supervised Learning, Model Training, and Machine Learning.
