COSC470: Special Topic - Machine Learning (2018)

Semester 2

Learning outcomes:

  1. An understanding of, an ability to use, and an ability to implement classical machine learning techniques (Information Literacy, Critical Thinking)
  2. An understanding of how AI agents play games and the most recent techniques for game playing (Information Literacy, Research, Critical Thinking, Lifelong Learning)
  3. An understanding of the basics of machine learning theory and how it applies to the recent success of deep learning (Information Literacy, Research, Critical Thinking)
  4. An ability to implement a deep learning model for a given task (Information Literacy, Critical Thinking, Research, Self-Motivation, Lifelong Learning)
  5. An understanding of the fundamentals of image recognition (Information Literacy, Critical Thinking, Research)
  6. An understanding of deep convolutional neural networks and an ability to use and implement such models (Information Literacy, Self-Motivation, Lifelong Learning)
  7. An ability to conduct AI experiments and successfully communicate the results (Information Literacy, Communication, Research, Lifelong Learning)
  8. An ability to find, read and understand recent research in the area (Information Literacy, Scholarship, Research, Lifelong Learning)
  9. An appreciation for the ethical problems associated with AI (Information Literacy, Ethics, Lifelong Learning)

Lecture outline:

  1. L1. Intro to classification and ML; decision trees
  2. L2. AdaBoost
  3. L3. SVMs
  4. L4. Basics of Learning Theory (and a bit of deep vs. shallow)
  5. L5. Deep Learning: classification/convnets/regularisation techniques etc.
  6. L6. Faces (Viola Jones detection and Eigenface recognition)
  7. L7. Convnets and image-based object recognition +
  8. L8. History of game playing, basic ideas, themes.
  9. L9. Deep reinforcement learning
  10. L10. The alphago breakthrough (and alphazero)
  11. L11. What next? [Are two player perfect information games just a solved case now? What are the more serious application cases?]
  12. L12. Issues with Face Recognition
  13. L13. Wrap-up, discussion of AI ethics.


  • Brendan McCane: L1-L3
  • Michael Albert: L8, L10, L11
  • Lech Szymanski: L4, L5, L9
  • Steven Mills: L6, L7, L12
  • Ali Knott and others: L13


Tuesday 9-11am