ECE 50024 / STAT 59800 Machine Learning

Spring 2024 Jan 8, 2024 - Apr 26, 2024

Recorded videos of the lectures can be found in Brightspace. The schedule is subject to change.

Week 1

• Jan 9, 2024. Lecture 0.
  • Topics: Course overview and linear regression I. Course Whiteboard
  • Reading:
    • Python Tutorial.
    • Python for Matrices. (Password is in BrightSpace.)
    • Python for Plotting. (Password is in BrightSpace.)
    • Linear Algebra Review.
    • Probability Review.
• Jan 11, 2024. Lecture 1.
  • Topics: Linear regression II. Course Whiteboard
  • Reading:
    • Week 1 Course Note

Week 2

• Jan 16, 2024. Lecture 2.
  • Topics: Linear regression examples. Course Whiteboard with explanation of pseudo-inverse solution of linear regression
  • Colab Demonstration - Legendre Polynomial, Autoregressive Model, and Outliers
  • Reading:
    • Keep reading Week 1 Course note.
• Jan 18, 2024. Lecture 3.
  • Topics: Outliers + Ridge Regression. Course Whiteboard
  • Reading:
    • Week 2 Course Note

Week 3

• Jan 23, 2024. Lecture 4.
  • Topics: LASSO Regression. Course Whiteboard
  • Colab Demonstration - Compression, Ridge Regression, LASSO, Shrinkage Operator
• Jan 25, 2024. Lecture 5.
  • Topics: Optimization I. Course Whiteboard
  • Reading:
    • Tutorial on Optimization.

Week 4

• Jan 30, 2024. Quiz 1.

• Feb 1, 2024. Lecture 6.

  • Topics: Optimization II. Course Whiteboard
  • Reading:
    • Week 3,4 Course Note

Week 5

• Feb 6, 2024. Lecture 7.
  • Topics: Optimization III. Linear Discriminant Analysis. Course Whiteboard
  • Reading:
    • Week 5 Course Note
    • Gradient Descent Demo
• Feb 8, 2024. Lecture 8.
  • Topics: Bayesian Decision Rule. Course Whiteboard
  • Reading:
    • Bayesian Decision Rule Demo

Week 6

• Feb 13, 2024. Lecture 9.
  • Topics: ROC Curve. Course Whiteboard
  • Reading:
    • Week 6 Course Note: ROC Curves
• Feb 15, 2024. Lecture 10.
  • Topics: Maximum Likelihood Estimation. Course Whiteboard
  • Reading:
    • Week 6 Course Note: Maximum Likelihood Estimation

Week 7

• Feb 20, 2024. Lecture 11.
  • Topics: Maximum-a-posteriori Estimation, Logistic Regression. Course Whiteboard
  • Reading:
    • Python Demo
    • Week 7 Course Note: Maximum-a-posteriori Estimation
    • Week 7 Course Note: Logistic Regression
• Feb 22, 2024. Lecture 12.
  • Topics: Logistic Regression, Kernel Method. Course Whiteboard
  • Reading:
    • Week 7 Course Note: Kernel Method
    • Python Demo: Logistic Regression

Week 8

• Feb 27, 2024. Lecture 13.
  • Topics: Kernel Method. Course Whiteboard
  • Reading:
    • Python Demo: Kernel Method
• Feb 29, 2024. Lecture 14.
  • Topics: Multi-layer Perceptron. Course Whiteboard
  • Reading:
    • Week 8 Course Note: Multi-layer Perceptron
    • Demo: Multi-layer Perceptron

Week 9

• Mar 5, 2024. Lecture 15.
  • Topics: Convolutional Neural Networks. Course Whiteboard
  • Reading:
    • Week 9 Course Note: Convolutional Neural Network
    • Demo: MNIST
• Mar 7, 2024. Seminar.

Week 10 Spring break.

Week 11

• Mar 19, 2024. Lecture 16.
  • Topics: Encoder-Decoder. Course Whiteboard
  • Reading:
    • Keep reading the course note of CNN.
    • Demo: Image Denoising MNIST
• Mar 21, 2024. Lecture 17.
  • Topics: Probability Inequality. Course Whiteboard

Week 12

• Mar 26, 2024. Lecture 18.
  • Topics: Is learning feasible? Course Whiteboard
  • Reading:
    • Week 12 Course Note: Learning feasibility
• Mar 28, 2024. Lecture 19.
  • Topics: Generalization Bound. Course Whiteboard
  • Reading:
    • Week 12 Course Note: Generalization bound

Week 13

• Apr 2, 2024. Lecture 20.
  • Topics: VC Dimension. Course Whiteboard
  • Reading:
    • Week 13 Course Note: VC Dimension
• Apr 4, 2024. Lecture 21.
  • Topics: Bias and Variance. Course Whiteboard
  • Reading:
    • Demo: Bias and Variance

Week 14

• Apr 9, 2024. Lecture 22.
  • Topics: Regularization. Course Whiteboard
  • Reading:
    • Week 14: Overfitting
    • Demo: Overfitting and Regularization
• Apr 11, 2024. Lecture 23.
  • Topics: Validation. Special Topic: Variational Autoencoder I. Course Whiteboard
  • Reading:
    • Demo: Validation

Week 15

• Apr 16, 2024. Lecture 24.
  • Special Topic: Variational Autoencoder II. Course Whiteboard
  • Reading:
    • Week 15: Expectation Maximization
• Apr 18, 2024. Lecture 25.
  • Special Topic: Variational Autoencoder III. Course Whiteboard

Week 16

• Apr 23, 2024. Lecture 26.
  • Special Topic: Variational Autoencoder IV. Course Whiteboard