EECE454: Introduction to ML Systems (Fall 2023)
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Team
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Location & Time
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- Class. Mondays/Wednesdays, 09:30AM–10:45AM @ 106 LG Hall
- Office Hr. Mondays, 04:00PM–05:00PM @ 407 Eng Bldg 2
Schedule (tentative)
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- W1. Introduction / Basic Linear Algebra
(9/4, 9/6) - W2. Basic Probability / Simple Models
(9/11, 9/13) - W3. Simple Models / Support Vector Machines
(9/18, 9/20) - W4. Kernel SVM / K-Means Clustering
(9/25, 9/27) - W5. Gaussian Mixture Models
(10/2, 10/4) - W6. Decision Tree
(10/9, 10/11) - W7. Dimensionality Reduction
(10/16, 10/18) - W8. Mid-Term
(10/23, 10/25) - W9. Deep Learning Basics / Convolutional Networks
(10/30, 11/1) - W10. Backprop / Neural Network Training
(11/6, 11/8) - W11. Neural Network Training / -
(11/13, 11/15) - W12. Deep ConvNets / Generative Models
(11/20, 11/22) - W13. Generative Models / Language Models
(11/27, 11/29) - W14. Language Models / Multimodal Learning
(12/4, 12/6) - W15. Efficient ML / Deep Learning Theory
(12/11, 12/13) - W16. Final Project Presentation
(12/18, 12/20)