Regression is a supervised learning technique designed for modeling and predicting continuous, numerical variables. This makes it ideal for scenarios such as forecasting real-estate prices, anticipating stock price fluctuations, or estimating student test scores. In contrast, classification is used for predicting categorical variables, like identifying employee turnover, detecting spam emails, uncovering financial fraud, or predicting student grades. Clustering, an unsupervised learning method, is utilized to discover natural groupings within data, applicable in areas like customer segmentation, e-commerce product grouping, and social network analysis. For more details, visit: Elite Data Science.