Introduction

Content

• Logistics

• Machine Learning Problems

  • Supervised Learning

  • Unsupervised Learning

• Performance Measures

  • Loss

  • Risk

  • Bayes Risk

• ML Applications

• Basic Statistics

  • Dependence

  • Independence

  • Conditional Independence

• Bayes Estimation

  • MLE estimation

  • MAP estimation

  • Naive Bayes classifier

Supplementary material

• Introduction slides in PDF

• MLE, MAP, and Bayes classification PDF

Recommended papers

• Alex Smola and S.V.N. Vishwanathan: Introduction to Machine Learning, Chapter I and II in PDF

• Tom Mitchell's 10701 lectures (Lectures 2,3,4)

• Tom Mitchell: Machine Learning, Chapter I in PDF

• Andrew Moore's Basic Probability Tutorial slides in PDF