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Table of Contents
Schedule
Announcements
Lecture videos are available at this CS480 video recordings site.
January
| Week | Topic | Material | Reading | Assignments |
|---|---|---|---|---|
| Week 1: Jan 17 - Jan 20 | Overview. Intro to machine learning. Python. | 01 Course Overview, 02 Matrices and Plotting, | The Great A.I. Awakening, by Gideon Lewis-Krause, NYT, Dec 14, 2016. Section 1 of Scipy Lecture Notes | |
| Week 2: Jan 23 - Jan 27 | Probability distributions and regression. | 03 Linear Regression, 04 Gaussian Distributions |
February
| Week | Topic | Material | Reading | Assignments |
|---|---|---|---|---|
| Week 3: Jan 30 - Feb 3 | Probabilistic Linear Regression. Ridge regression. Data partitioning. On-line, incremental regression. | 05 Fitting Gaussians, 06 Probabilistic Linear Regression, 07 Linear Ridge Regression and Data Partitioning, 08 Sample-by-Sample Linear Regression | A1 Linear Regression due Monday, January 30th at 10:00 PM. | |
| Week 4: Feb 6 - Feb 10 | Regression with fixed nonlinearities. Nonlinear regression with neural networks. Feb 10: Guest Speaker Mike Morain, Machine Learning at Amazon, UK. | 09 Linear Regression with Fixed Nonlinear Features, 10 Nonlinear Regression with Neural Networks.ipynb | ||
| Week 5: Feb 13 - Feb 17 | Neural Networks | 10 Nonlinear Regression with Neural Networks.ipynb, 11 More Nonlinear Regression with Neural Networks | A2 Ridge Regression with K-Fold Cross-Validation due Monday, February 13th at 10:00 PM. | |
| Week 6: Feb 20 - Feb 24 | ||||
| Week 7: Feb 27 - Mar 3 | A3 Neural Network Regression due Wednesday, March 1st at 10:00 PM. |
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