Gentle Introduction to Logistic Regression. We explore this powerful yet simple machine learning model for binary classification tasks like predicting whether a student will pass or fail an exam! We’ll explain the difference between logistic and linear regression, dive into the intuition behind the sigmoid function, and uncover why cross-entropy loss makes sense for probability-based models. No complex math needed—just clear explanations, intuitive visuals, and a practical demo in Python with scikit-learn. --------------- 00:00 Introduction 00:30 Working example 1:06 Review of Linear Regression 2:33 Logistic Regression 3:30 Cross-entropy loss function 7:10 Code This video would not have been possible without the help of Gökçe Dayanıklı.