This tutorial provides comprehensive lecture notes on regression analysis, covering fundamental concepts from linear models to deep learning. It aims to equip students with a solid understanding of various regression models, including linear, logistic, and Softmax regression, along with essential methodologies like loss function design, parameter estimation, and regularization techniques, bridging classical statistics and modern machine learning practices.