3F3: Signal and Pattern Processing

Zoubin Ghahramani
5 Lectures on Pattern Processing and Machine Learning

Lecture Notes:

• Lecture 1: Introduction
  
• Lecture 2: Regression
  
• Lecture 3: Classification
  
• Lecture 4: Clustering
  
• Lecture 5: Dimensionality Reduction
  

• Examples Paper

• Online Linear Logistic Classification: lrdemo.m
• Online Non-linear Logistic Classification: nlrdemo.m
• K-means Clustering: kmeansdemo.m
• Iris Data: iris.data (needed for K-means demo)

If you are interested in this topic, you may want to look at 4F10: Statistical Pattern Processing and 4F13: Machine Learning modules.