STA 414/2104 (Fall 2015): Statistical Methods for Machine Learning and Data Mining - Lecture Schedule

Tentative Lecture Schedule

• Lecture 1 -- Machine Learning:
  Introduction to Machine Learning, Probability Distributions (notes [pdf])
  Reading: Bishop, Chapter 1: sec. 1.1 - 1.3
  
  
• Lecture 2 -- Probability Distributions:
  (notes [pdf])
  Reading: Bishop, Chapter 2: sec. 2.1 - 2.4
  
  
• Lecture 3 -- Regression (notes [pdf])
  Reading: Bishop, Chapter 1: sec. 1.5
  Chapter 3: sec. 3.1 - 3.2
  
  
• Lecture 4 -- Bayesian inference (notes [pdf])
  Reading: Bishop, Chapter 3: sec. 3.3 - 3.5
  
  
• Lecture 5 -- Classification (notes [pdf])
  Reading: Bishop, Chapter 4: sec. 4.1 - 4.5
  
  
• Lecture 6 -- Gaussian Processes (notes [pdf])
  Reading: Bishop, Chapter 6: sec. 6.4
  
  
• Lecture 7 -- Mixture Models (notes [pdf])
  Reading: Bishop, Chapter 9: sec. 9.1 - 9.3.
  
  
• Lecture 8 -- Latent Variable Models (notes [pdf])
  Reading: Bishop, Chapter 12: sec. 12.1 - 12.2, 12.4
  
  
• Lecture 9 -- Modeling Sequential Data (notes [pdf])
  Reading: Bishop, Chapter 13: sec. 13.1 - 13.2.
  
  
• Lecture 10 -- Wrap-up and Final Review (notes [pdf])

STA 414/2104 (Fall 2015): Statistical Methods for Machine Learning and Data Mining || http://www.cs.toronto.edu/~rsalakhu/STA414_2015/