ECE 595 / STAT 598: Lecture

This schedule is for Spring 2021.

Week 1 Jan 19 - 21, 2021

  • Jan 19, 2021. Lecture 0. Course overview. Mathematics review.

    • Live video recording (2021): Available in Brightspace.

    • Please review Tutorials 0, 6, 7 (See below)

  • Jan 21, 2021. Lecture 1. Linear regression.

    • Past videos (2020): (PDF) Linear Regression Concepts and Geometry (Video 1) (Video 2)

    • See Chapter 7.1 of my book (URL)

    • Please review Tutorials 1 and 2 (See below)

    • Python demo for linear regression (URL)

Week 2, Jan 26 - 28, 2021

  • Jan 26, 2021. Lecture 2. Outliers in linear regression

    • Hand writte note

    • Live video recording (2021): Available in Brightspace.

    • See Chapter 7.1 of my book (URL)

    • Please review Tutorials 3 (See below)

    • Python demo for linear regression with outliers (URL)

  • Jan 28, 2021. Lecture 3. Ridge and LASSO Regularization

Week 3, Feb 2 - 4, 2021

  • Feb 2, 2021. Lecture 4. Optimization: Concepts

  • Feb 4, 2021. Lecture 5. Optimization: Algorithms

    • Hand written note

    • Past videos (2020): (PDF) Optimization 2: Gradient Descent and Stochastic Gradient Descent (Video 1) (Video 2)

    • Read the references in reading list page of the slides (PDF)

    • Please review Tutorials 4 (See below)

    • Python demo for gradient descent (URL)

Week 4, Feb 9 - 11, 2021

  • Feb 9, 2021. Lecture 6. Linearly Separable

    • Hand written note

    • Past videos (2020): (PDF) Linear Separability (Video 1) (Video 2)

    • Read the references in reading list page of the slides (PDF)

    • The proof of the separating hyperplane theorem is optional, but you are welcome to read.

    • Python demo for constrained optimization (URL)

Week 5, Feb 16 - 18, 2021

  • Feb 16, 2021. Lecture 8. Bayesian Classifier 2

    • Hand written note

    • Past videos (2020): (PDF) Bayesian Decision Rule (Video 2) (Video 3)

    • Past videos (2020): (PDF) Generative Method 2: Minimum Probility of Error Rule (Video) (First 30 minutes)

    • Read the references in reading list page of the slides (PDF)

    • Python demo for Bayesian decision rule (URL)

  • Feb 18, 2021. Lecture 9. Classification Error / ROC Curve

    • Hand written note

    • Past videos (2020): (PDF) Generative Method 2: Minimum Probility of Error Rule (Video) (Second 30 minutes)

    • Read the references in reading list page of the slides (PDF)

    • See Chapter Chapter 9.5 of my book (URL)

    • Python demo for ROC (URL)

Week 6, Feb 23 - 25, 2021

Week 7, Mar 2 - Mar 4, 2021

  • Mar 4, 2021. Lecture 13. Kernel trick

Tutorials

  • Tutorial 0 Python Basics (PDF)

  • Tutorial 1 Linear Algebra Review (PDF)

  • Tutorial 2 Probability Review (PDF)

  • Tutorial 3 Linear Regression Examples (PDF)

  • Tutorial 4 Optimization Review (PDF)

  • Tutorial 5 Python for Image Processing (URL) (Password is in Brightspace)

  • Tutorial 6 Python for Matrices (URL) (Password is in Brightspace)

  • Tutorial 7 Python for Plotting (URL) (Password is in Brightspace)