Lectures (for both COMP307 and AIML420)

NB!! The lectures and tutorials are live-streamed (on a best-effort basis) through Zoom: https://vuw.zoom.us/my/comp307. All lectures are also recorded and can be watched through Blackboard.

Week num Topic Resources
1 1 Introduction PDF
2 Search (1/2): "Classic" Search Algorithms PDF
  Tutorial 1: History of AI Scan
2 3 Search (2/2): Local Search, Beam Search, and Other Considerations PDF
4 Machine Learning (1): Basics, types, paradigms, training set vs test set, generalisation PDF pptx
  Tutorial 2 PDF pptx
3 5 Machine Learning (2): K-Nearest Neighbour, K-Means, and K-fold Cross Validation PDF pptx
6 Machine Learning (3): Decision tree learning method PDF pptx
  Tutorial 3 PDF pptx
4 7 Neural Networks (1): Perceptron learning PDF pptx Scan
8 Neural Networks (2): Back Propogation PDF pptx
  Tutorial 4 PDF pptx
  Walking through an example of feedforward and backpropagation from class Link PDF Video
5 9 Neural Networks (3): Neural Engineering PDF pptx
10 Evolutionary Computation (1): Evolutionary Computation and Learning PDF pptx
  Tutorial 5 A1 Q&A
6 11 Evolutionary Computation (2): Genetic Programming PDF pptx
12 Evolutionary Computation (3): Genetic Programming for Regression and Classification PDF pptx
  Tutorial 6 A2, General Q&A
Trimester Break
7 13 Lecture  
14 Lecture  
  Tutorial 7  
  Midterm Test! 21 Apr (Wed) 18:00-19:00 Last Name A-K: MCLT101 Last Name L-Z: MCLT103

A2, General Q&