Unsupervised Learning

Unsupervised Learning Tasks

• Clustering: Groups similar data points together (e.g. customer segmentation). Algorithms like K-means, hierarchical clustering, and DBSCAN are commonly used.

• Dimensionality Reduction: Reduces the number of features in a dataset while retaining important information, making the data easier to visualize or process. Principal Component Analysis (PCA) and T-SNE are common techniques.