Regression is a supervised learning technique used to predict continuous output based on input features.Linear regression is a widely used algorithm that establishes a relationship between dependent and independent variables.Optimization techniques like Gradient Descent are used to find the best-fit parameters in linear regression.Ridge regression and Lasso regression are regularization techniques used to improve the performance of linear regression.