Coursera-Machine-Learning-Stanford

This repo contains the solutions of quizes and assignments of Coursera's Andrew Ng Stanford Machine Learning course

Machine Learning by Stanford University

Week 1: Linear Regression with One Variable

• Parameter Learning

Week 2: Linear Regression with Multiple Variables

• Multivariate Linear Regression • Computing Parameters Analytically

Week 3: Logistic Regression

• Classification and Representation • Logistic Regression Model • Multiclass Classification • Regularization • Solving the Problem of Overfitting

Week 4: Neural Networks: Representation

• Neural Networks • Applications

Week 5: Neural Networks: Learning

• Neural Networks: Learning • Cost Function and Backpropagation • Backpropagation in Practice • Application of Neural Networks

Week 6: Evaluating a Learning Algorithm

• Bias vs. Variance • Machine Learning System Design • Using Large Data Sets

Week 7: Support Vector Machines

• Large Margin Classification • Kernels • SVMs in Practice

Week 8: Unsupervised Learning

• Clustering • Dimensionality Reduction • Principal Component Analysis

Week 9: Anomaly Detection

• Density Estimation • Building an Anomaly Detection System • Multivariate Gaussian Distribution (Optional) • Recommender Systems • Predicting Movie Ratings • Collaborative Filtering • Low Rank Matrix Factorization

Week 10: Large Scale Machine Learning

• Gradient Descent with Large Datasets • Advanced Topics

Week 11: Application Example: Photo OCR

• Photo OCR