Schedule (Fall 2022)

Lectures

• Introduction to CSC 461, The Badges Game [PDF] [Colab]

  • Required reading: Google's Python Class
  • Required reading: Linear Algebra Lecture @ Stanford's CS229

• Introduction Machine Learning [PDF]

  • Required reading: Python Numpy Tutorial

• Unsupervised Learning, Clustering, K-Means [PDF] [Colab]

  • Required reading: Section 22.2 from UML

• Hierarchical Clustering [PDF]

  • Required reading: Section 12.4 from ISL

• Principal Component Analysis [PDF] [Colab]

  • Required reading: Section 12.1 from PRML

• Introduction to Supervised Learning [PDF] [Colab]

  • Required reading: Part I from CS229 lecture notes @ Stanford or CS4780 lecture notes @ Cornell

• Linear Regression [PDF] [Colab]

  • Required reading: Chapter 1 from Stanford's CS229 Lecture Notes

• Nonlinear Features, Overfitting, Regularization, Model Selection [PDF] [Colab]

  • Required reading: Section 1.1 from PRML
  • Required reading: Practical Issues

• Gradient Descent [PDF] [Colab]

  • Required reading: Chapter 6 from IDA

• Gradient Descent and Machine Learning, Stochastic Gradient Descent [PDF] [Colab]

  • Required reading: Chapter 5 from DL

• Feedback Session [PDF]

• Linear Classifiers and Logistic Regression [PDF] [Colab]

  • Required reading: Sections 4.1, 4.2 from PRML

• Multinomial Logistic Regression [PDF]

  • Required reading: Section 4.3 from PRML

• Evaluation and Model Selection, Perceptron [PDF]

• Multilayer Perceptrons [PDF] [Colab-1] [Colab-2]

  • slides used in class borrowed from: CS231n @ Stanford
  • Required reading: Chapter 6 from DL

• k-NN Classification [PDF]

  • Required Reading: Geometry and Nearest Neighbors

• Decision Trees [PDF]

  • Required Reading: Decision Trees

• Bagging [PDF]

• Boosting [PDF]

  • Required Reading: Ensemble Methods

Important dates

• Assignment 1 (due Sep 23rd)
• Assignment 2 (due Oct 3rd)
• Assignment 3 (due Nov 2nd)
• Assignment 4 (due Oct 25th)
• Assignment 5 (due Dec 7th)
• Assignment 6 and optional part 7 (due Dec 13th) -- late submissions until Dec 20th
• Midterm Exam 1 (Oct 26th)
• Midterm Exam 2 (Nov 23rd)

Project

• Progress report (due Nov 16th)
• Final report (due Dec 20th)
• Github Repo (due Dec 20th)
• Project Presentation (due Dec 20th)