Lectures take place on Mondays and Wednesdays where students will engage in lectures given by Professor Taylor and guest lectures. Lectures are on Monday from 1:25PM – 2:40PM ET, Bloomberg 61X and will cover these topics:
- Dataset Curation
- Building an End-to-End ML Pipeline
- Regression for Predicting Housing Prices
- Clustering for Document Retrieval
- Classification for Product Recommendation
- Deep Learning for Image Search
Guest lectures will be given by experts working in AI and ML.
Students have 6 late days to use for the semester for assignment submissions (maximum of 2 per assignment), including homework and the final project. After that, the grade will be dropped one letter grade per day late. No exceptions.
Students have 1 week after assignments are returned to make a regrade request (no exceptions). Send an email to Prof. Taylor and Olga.
Course Schedule
| Week # | Lecture (M) | Lecture (W) |
| 1: Week of 1/22 | Lecture 1: Introduction to PAML | Lecture 2: Revisit Preliminaries |
| 2: Week of 1/29 | Lecture 3: Building an End-to-End ML Pipeline I | Lecture 4: Dataset Curation |
| 3: Week of 2/5 | Lecture 5: Data Preprocessing I | Lecture 6: Data Preprocessing II |
| 4: Week of 2/12 | Lecture 7: Introduction to Regression I | Lecture 8: Introduction to Regression II |
| 5: Week of 2/19 | Lecture 9: Regression for Predicting Housing Prices | Lecture 10: Regression for Predicting Housing Prices |
| 6: Week of 2/26 | No Class – February Break | Homework Review |
| 7: Week of 3/4 | Lecture 11: Introduction to Classification | Lecture 12: Classification for Product Recommendation |
| 8: Week of 3/11 | Lecture 13: Classification for Product Recommendation [REMOTE LECTURE] | Lecture 14: Classification for Product Recommendation [REMOTE LECTURE] |
| 9: Week of 3/18 | Lecture 15: Introduction to Clustering | Lecture 16: Clustering for Document Retrieval |
| 10: Week of 3/25 | Lecture 17: Clustering for Document Retrieval | Lecture 18: Clustering for Document Retrieval |
| 11: Week of 4/1 | No Class – Spring Break | No Class – Spring Break |
| 12: Week of 4/8 | Lecture 19: Deep Learning Fundamentals I | Lecture 20: Deep Learning for Image Search |
| 13: Week of 4/15 | Lecture 21: Final Project Discussion | Guest Lecture – FP Working Day |
| 14: Week of 4/22 | Guest Lecture – Tariq Iqbal (UVA) | Guest Lecture – Kilian Weinberger (Cornell) |
| 15: Week of 4/29 | Guest Lecture – Karen Levy (Cornell) | FP Midpoint Report |
| 16: Week of 5/6 | Last Day of Instruction | No Class |
| 17: Week of 5/13 | Final Project Presentation | Final Project Report & Code Due |