ml ยป


Supervised Learning
Jan 15Course Start Date
Jan 17Decision Trees
  • Mitchell Ch 3
Jan 19Regression and Classification
Jan 21Neural Networks
  • Mitchell Ch 4
Jan 24Instance Based Learning
  • Mitchell Ch 8
Jan 28Ensemble Learning
Jan 31Kernel Methods and Support Vector Machines
Feb 4Computational Learning Theory
  • Mitchell Ch 5, 7
Feb 7VC Dimensions
Feb 11Bayesian Learning
  • Mitchell Ch 6
Feb 14Bayesian Inference
Feb 14Assignment 1 due (Submit on T-square)
Feb 21Midterm. Time: TBD (changed from Feb 18)
Unsupervised Learning
Feb 23Randomized Optimization
  • Mitchell Ch 9
Feb 25Clustering and EM
Feb 28Feature Selection
Mar 7Feature Transformation
Mar 14Information Theory
Mar 30Assignment 2 due (Submit on T-square)
Reinforcement Learning
Apr 4Markov Decision Processes
Apr 8Reinforcement Learning
Apr 11Game Theory
Apr 15Game Theory Continued
Apr 20Assignment 3 due (Submit on T-square)
Apr 28Final Exam. Time: TBD

Note: Dates indicate deadlines by which you should finish each lesson, assignment or exam.