Understanding Logistic Regression: A Beginner's Guide to Binary Classification 🔍

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.