Python implementations of the exercises presented by Andrew Ng in "Machine Learning" class on Coursera. You may find more details in Russian at timofey.pro Week 1: Linear Regression with One Variable Week1: Solution using Pandas and Numpy Week1: Solution using scikit-learn Week2: Linear Regression with multiple variables Week2: Solution using Numpy and feature normalization Week2: Same solution using Normal Equation Week3: Logistic Regression Week3: Solution using Gradient Descent Week3: Same solution using Scikit-Learn Week3: Microchips solution (adding additional higher order polynomial features) Week4: One-vs-All + Neural Networks Week 5: Backpropagation