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COMP3608 - Intelligent Systems

Course Outline

Quiz

Psets

  1. Pset 1 Solutions

Assignemnts

  1. A1
  2. A2

Week #13 - Recap and Epilogue

Week #12 - No class, Good Friday

Week #11 - Bayes Networks and Bayes Thereom Part 2

  • Recommended Reading: Murphy, Chapter 10

Week #10 - Bayes Networks and Bayes Thereom Part 1

  • Recommended Reading: Murphy, Chapter 10

Week #9 - Convolutional Neural Networks

Week #8 - Feed-foward Neural Networks

Week #7 - Linear Regression and Logistic Regression

Week #6 - Machine Learning Basics Continued

  • Recommended Reading: Flach, Chapter 1
  • Slides

Week #5 - Machine Learning Basics

Week #4 - Metaheuristics Continued, Maximum Liklihood Estimation, Data Fitting, and Gradient Descent Lab

Week #3 - Metaheuristics and MiniZinc

Week #2 - Optimization Concepts and Mathematical Preliminaries

  • Recommended Reading: Kochenderfer and Wheeler Chapters 1 and 2
  • Recommended Reading: Deisenroth et al.
    • Sections 2.1 - 2.4
    • Sections 3.1 - 3.3
    • Sections 5.1 - 5.4
    • Sections 6.1 - 6.3
  • Slides - Lecture
  • Lab

Week #1 - Intro to AI and Course Outline

  • Recommended Reading: Russel and Norvig Chapters 1 and 2
  • Slides

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Languages

  • Jupyter Notebook 98.8%
  • Python 1.2%