Learning from unlabeled data to find patterns.
Algorithms: K-Means Clustering, Principal Component Analysis (PCA), Autoencoders.
Applications: Customer segmentation, anomaly detection, recommendation systems.
Sub Tracks:
Clustering
Dimensionality Reduction
Association Rule Learning
Anomaly Detection