Learn how to implement a Logistic Regression model in Python using just math and NumPy (no machine learning libraries like Scikit-Learn). I’ll walk through the core math behind logistic regression, including the sigmoid function, decision boundaries, and the cost function, and then show how to turn those equations into code. This is Episode 2 of my Machine Learning From Scratch series, where I’m building ML algorithms from the ground up, step-by-step to truly understand how they work under the hood. 📺 Watch the Playlist Here: 💻 Full Code on GitHub: TIMESTAMPS: 00:00 - Introduction 00:21 - PART 1: The Math 09:50 - PART 2: Coding it up #machinelearning #python