Key Types and How They Work
Trains models using labeled data to predict outcomes accurately.
Analyzes unlabeled data to discover hidden patterns and relationships.
Combines labeled and unlabeled data for improved learning efficiency.
Teaches agents through trial and error, optimizing actions via rewards.
A supervised method categorizing data into predefined classes.
Predicts continuous values based on input features in supervised learning.
Groups similar data points in unsupervised learning for insights.