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