Schedule
This is a tentative syllabus and schedule. Topics, reading assignments, due dates, and exam dates are subject to change. All assignments and projects are due by 11:59:59pm Eastern time on the day listed.
The readings will come from Machine Learning (Flach), Learning from Data (LfD), the reading packet (Handout), or online sources.
Recordings of the lectures are available online via Canvas.
| Week | Date | Topic | Recitation | Assignments | Notes | |
|---|---|---|---|---|---|---|
| Mon 08/27 | HW 0 out (due on 09/04) | |||||
| Wed 08/29 | No Class | |||||
| Mon 09/03 | Labor Day - No Class | |||||
| Tues 09/04 | HW 0 due | |||||
| 1 | Wed 09/05 | Lecture #0: Introduction to CIS 419/519 [pptx] [pdf] [video] | Sign up for Piazza |
A Machine Learning Puzzle Some Readings: 1. deep-learning-isnt-dangerous-magic-genie-just-math/ 2. artificial-intelligence-challenges.html 3. Deep Learning: A Critical Appraisal 4. Roth-incidental-supervision.pdf |
||
| 2 | Mon 09/10 | Lecture #1: Introduction to Machine Learning [pptx] [pdf] [video] | ||||
| Wed 09/12 | Introduction to Python [html] [ipynb] [video] | Recitation #1 [colab] | ||||
| Thurs 09/13 | Recitation #1 [colab] | Quiz 1 out (due Sun 09/16) | ||||
| 3 | Mon 09/17 | Lecture #1: Introduction to Machine Learning [pptx] [pdf] [video] | ||||
| Course Selection Period Ends | ||||||
| Wed 09/19 | Yom Kippur - No Class | |||||
| 4 | Mon 09/24 | Lecture #2: Decision Trees; Over-fitting [pptx] [pdf] [video] | Efficient Learning of Linear Perceptrons | |||
| Wed 09/26 | Lecture #2: Decision Trees; Over-fitting [pptx] [pdf] [video] | Recitation #2: Python Session - 2 [pptx] [pdf] | HW 1 out (due Tues 10/09) | |||
| Thurs 09/27 | Recitation #2: Python Session - 2 [pptx] [pdf] | Quiz 2 out (due Sun 09/30) | ||||
| 5 | Mon 10/01 | Lecture #3: Evaluation [pptx] [pdf] [video] | ||||
| Wed 10/03 | Lecture #4: On-line Learning, Perceptron, Kernels [pptx] [pdf] [video] | Recitation #3 [pptx] | ||||
| 6 | Mon 10/08 | Lecture #4: On-line Learning, Perceptron, Kernels [pptx] [pdf] [video] | ||||
| Drop Period Ends | ||||||
| Wed 10/10 | Lecture #4: On-line Learning, Perceptron, Kernels [pptx] [pdf] [video] | Recitation #4 [GitHub] [ipynb] | HW 2 out (due Sun 10/24) | Large Margins Using Perceptron | ||
| Thurs 10/11 | Recitation #4 [GitHub] [ipynb] | Quiz 3 out (due Sun 10/14) | ||||
| Mon 10/15 | Class canceled | |||||
| 7 | Wed 10/17 | Lecture #5: Why Machine Learning Works: Explaining Generalization [pptx] [pdf] [video] | Recitation #5 [GitHub] [ipynb] [video] | |||
| Thurs 10/18 | Recitation #5 [GitHub] [ipynb] | Quiz 4 out (due Sun 10/21) | ||||
| 8 | Mon 10/22 | Lecture #5: Why Machine Learning Works: Explaining Generalization [pptx] [pdf] [video] | ||||
| Wed 10/24 | Lecture #6: Support Vector Machine [pptx] [pdf] [video] | |||||
| 9 | Mon 10/29 | Lecture #7: Boosting and Ensembles; Multi-class Classification and Ranking [pptx] [pdf] [video] | Midterm Review [slides] | |||
| Wed 10/31 | Midterm Exam | [CIS519 Midterm Fall16], [CIS519 Midterm Fall17], [CS446 Midterm Spring17], [CIS519 Midterm Spring18] [CIS519 Midterm Fall18] | ||||
| 10 | Mon 11/05 |
Lecture #8: Neural Networks and Deep Learning
[pptx]
[pdf]
[video]
Friday 3:00pm-4:00pm
|
||||
| Wed 11/07 | Lecture #8: Neural Networks and Deep Learning [pptx] [pdf] [video] | Recitation #7 | HW 3 out (due Mon 11/19) | |||
| Thurs 11/08 | Recitation #7 | Quiz 6 out (due Sun 11/11) | ||||
| Fri 11/09 | Last day to withdraw | |||||
| 11 | Mon 11/12 | Lecture #6: Support Vector Machine [pptx] [pdf] [video] | ||||
| Wed 11/14 | Lecture #7: Boosting and Ensembles; Multi-class Classification and Ranking [pptx] [pdf] [video] | Recitation #8 [pptx] | ||||
| Thurs 11/15 | Recitation #8 | Quiz 7 out (due Sun 11/18) | ||||
| 12 | Mon 11/19 | Lecture #9: Generative Models; Naive Bayes [pptx] [pdf] [video] | ||||
| Wed 11/21 | Lecture #9: Generative Models; Naive Bayes [pptx] [pdf] [video] | HW 4 out (due Sun 12/02) | ||||
| 13 | Mon 11/26 | Lecture #10: Un/Semi-Supervised Learning: EM and K-Means [pptx] [pdf] [video] | ||||
| Wed 11/28 | Lecture #11: Bayesian Networks [pptx] [pdf] [video] | Recitation #9 | ||||
| Thurs 11/29 | Recitation #9 | Quiz 8 out (due Sun 12/02) | ||||
| 14 | Mon 12/03 | Lecture #11: Bayesian Networks [pptx] [pdf] [video] | ||||
| Wed 12/05 | Lecture #12: Clustering / Dimensionality Reduction [pptx] [pdf] [video] | Recitation #10 | HW 5 out (due Mon 12/10) | |||
| Thurs 12/06 | Recitation #10 | Quiz 9 out (due Sun 12/09) | ||||
| 15 | Mon 12/10 | Project Poster Session | ||||
| 16 | Mon 12/17 | Final Exam (12-2pm) @CHEM 102 | Appendix | [CS446 Final 2012], [CS446 Final 2012 Solutions], [CS446 Final 2016], [CS446 Final 2016 Solutions] | ||
| Thurs 12/20 | Final Project Reports Due | |||||