Solutions to the Programming Assignments from Andrew Ng Machine Learning Stanford Class 1/7/2017 - 3/26/2017
Assignments were completed with GNU Octave, version 3.8.0
Course Schedule Week 1
Introduction
Linear Regression with One Variable
(Optional) Linear Algebra Review
Week 2
Linear Regression with Multiple Variables
Octave Tutorial
Programming Exercise 1 (Linear regression)
Week 3
Logistic Regression
Regularization
Programming Exercise 2 (Logistic regression)
Week 4
Neural Networks: Representation
Programming Exercise 3 (Multi-class classification and neural networks)
Week 5
Neural Networks: Learning
Programming Exercise (Neural network learning)
Week 6
Advice for Applying Machine Learning
Machine Learning System Design
Programming Exercise (Bias-variance)
Week 7
Support Vector Machines (SVMs)
Programming Exercise (SVMs)
Week 8
Clustering
Dimensionality Reduction
Programming Exercise (K-Means and PCA)
Week 9
Anomaly Detection
Recommender Systems
Programming Exercise (Anomaly Detection and Recommender Systems)
Week 10
Large-Scale Machine Learning
Aplication Example: Photo OCR