Machine-Learning-Andrew-Ng

The handouts and exercises of Andrew Ng's Machine Learning course

Week 1

Lecture1 Introduction

Lecture2 Linear regression with one variable

Lecture3 Linear Algebra review(optional)

Week 2

Lecture4 Linear Regression with Multiple Variables

Lecture5 Octave/Matlab Tutorial

machine-learning-ex1 Linear Regression

Week 3

Lecture6 Logistic Regression

Lecture7 Regularization

machine-learning-ex2 Logistic Regression

Week 4

Lecture8 Neural Networks: Representation

machine-learning-ex3 Multi-class Classification and Neural Networks

Week 5

Lecture9 Neural Networks: Learning

machine-learning-ex4 Neural Networks Learning

Week 6

Lecture10 Advice for Applying Machine Learning

Lecture11 Machine learning system design

machine-learning-ex5 Regularized Linear Regression and Bias/Variance

Week 7

Lecture12 Support Vector Machines

machine-learning-ex6 Support Vector Machines

Week 8

Lecture13 Unsupervised Learning

Lecture14 Dimensionality Reduction

machine-learning-ex7 K-Means Clustering and PCA

Week 9

Lecture15 Anomaly detection

Lecture16 Recommender Systems

machine-learning-ex8 Anomaly Detection and Recommender Systems

Week 10

Lecture17 Large scale machine learning

Week 11

Lecture18 Application Example: Photo OCR