CSCI 335: Machine Learning
Week | Topics | Deliverables | Notes | Sources |
---|---|---|---|---|
1 Aug 28 | Overview: What exactly is Machine Learning? Classification vs. Regression: Selection vs. Scoring | First Lecture Tues Aug 29 | * Hastie Ch. 1, 2.1-2.3 | |
2 Sept 4 | Least Squares: Parametric linear regression and classification model k-Nearest Neighbors: Non-parametric regression and classification model | Quiz 1 | Add/Drop Ends Tues Sept 5 | |
3 Sept 11 | Bayesian Decision Theory Example: parametric models using Gaussian feature distributions | Assign 1 | Readings in MyCourses: * Charniak SLL Ch 2 * DuinEtAl Ch 2 | |
4 Sept 18 | Bayesian Decision Theory (continued) | Quiz 2 | ||
5 Sept 25 | Neural Networks: Overview Loss functions & Backpropagation Example Neuron: 'Classic' Perceptron | Career Fair (link) Sept 27/28 (Wed/Th) | Charniak DL Chs 1 and 2 | |
6 Oct 2 | Neural Networks: Backpropagation & Autogradient Data use and training networks | Quiz 3 Assign 2 | ||
*7 Oct 9 | Neural Net Implementation in TensorFlow | Quiz 4 | Fall Break No classes Mon/Tues | |
8 Oct 16 | Convolutional Networks | Quiz 5 | Project Assigned Groups set on Friday | Charniak DL, Ch 3 |
9 Oct 23 | Convolutional Networks (continued) | Quiz 6 | 'Shopping carts' open for spring registration | |
10 Oct 30 | Recurrent Networks | Quiz 7 Assign 3 | Charniak DL, Ch 4 | |
11 Nov 6 | Recurrent Networks (continued) | Project Proposal Quiz 8 | ||
12 Nov 13 | Recurrent Nets (continued, II) | Quiz 9 | Project Proposal: Feedback returned * Registration starts | Charniak DL, Ch. 5 |
*13 Nov 20 | Seq-to-Seq models | Holiday Break No class on Thursday | ||
14 Nov 27 | Additional Topics Final Project Discussions | Quiz 10 | *Open registration | Charniak DL, Ch. 6/7 (excerpts) |
15 Dec 4 | Additional Topics Final Project Discussions Review and Next Steps | Assign 4 | Final Lecture Thurs Dec 7 | |
*16 Dec 11 | *Wk 1 Exams |
Final Project | Reading Day: Tues Dec 12 Fri Dec 15 1:30-4pm | |
*17 Dec 18 | *Wk 2 Exams | Exams End Wed Dec 20 |