Building Logistic Regression from Scratch: A Complete Python Implementation
Introduction Understanding machine learning algorithms at their core is crucial for any data scientist. In this comprehensive tutorial, we’ll build logistic regression entirely from scratch using Python and NumPy. No black-box libraries, just the math implemented in code. We’ll use everything from the sigmoid function and cross-entropy loss to gradient descent optimization. Finally, we’ll test our implementation on the classic “moons” dataset to validate our approach. The Mathematical Foundation Logistic regression transforms linear combinations of features into probabilities using the sigmoid function: ...