Machine-Learning

Coursera - Stanford Course on Machine Learning published under my RPubs repository and GitHub repository

Includes lecture notes and programming exercises with commands to run the following MATLAB/Octave scripts.

Each directory contains a pdf document with instructions and more detailed analyses for each exercise.

Lecture Notes

• Machine Learning : Week 1 - Introduction
• Machine Learning : Week 2 - Linear Regression with Multiple Variables
• Machine Learning : Week 3 - Logistic Regression
• Machine Learning : Week 4 - Neural Networks
• Machine Learning : Week 5 - Neural Networks - Learning
• Machine Learning : Week 6 - Regularlized Linear Regression and Bias v.s. Variance
• Machine Learning : Week 7 - Support Vector Machines
• Machine Learning : Week 8 - Unsupervised Learning
• Machine Learning : Week 9 - Anomaly Detection and Recommender Systems
• Machine Learning : Week 10 - Large Scale Machine Learning

Exercises

• Machine Learning : Exercise 1 - Linear Regression

  • Commands: run ex1.m

• Machine Learning : Exercise 2 - Logistic Regression

  • Commands: run ex2.m

• Machine Learning : Exercise 3 - Multi-Class Classification and Neural Networks

  • Commands: run ex3.m

• Machine Learning : Exercise 4 - Neural Networks - Learning

  • Commands: run ex4.m

• Machine Learning : Exercise 5 - Machine Learning: Regularized Linear Regression and Bias v.s. Variance

  • Commands: run ex5.m

• Machine Learning : Exercise 6 - Support Vector Machines

  • Commands: run ex6.m

• Machine Learning : Exercise 7 - K-means Clustering and Principal Component Analysis

  • Commands: run ex7.m

• Machine Learning : Exercise 8 - Anomaly Detection and Recommender Systems

  • Commands: run ex8.m

-Sulman Khan