Skip to content


The goal of assignments is to assess students’ understanding of the course outcomes in homework and final project assignments. The assignment deadlines are due on Gradescope and as follows:


  • Homeworks: Coding assignments on course topics are DUE 2 weeks after assigned.
  • Final Project Proposal: Propose an FP idea; DUE on April 26th @ 11:59PM. 
  • Final Project Midpoint Report: Provide updates on project deliverables on May 1st during the class session. 
  • Final Project Presentation: Present FP in class for 15 minutes with a 3-minute Q&A; scheduled on May 13th @ 2:40PM. 

Late Policy

Students have 6 late days (2 max per assignment) to use for the semester for assignment submissions, including homework and the final project. After that, the grade will be dropped one letter grade per day late. 

Students have 1 week after assignments are returned to make a regrade request (no exceptions). Send an email to Prof. Taylor, Jinzhao Kang, and Kathryn Guda.=

Course Assignment Schedule


Week # Lecture (M) Lecture (W)
1: Week of 1/22 Lecture 1: Introduction to PAML (Homework 0) Lecture 2: Revisit Preliminaries
2: Week of 1/29 Lecture 3: Building an End-to-End ML Pipeline  Lecture 4: Dataset Curation (Homework 0 DUE)
3: Week of 2/5 Lecture 5: Preprocessing I 


Lecture 6: Preprocessing II (In-class activities)

(Homework 1)

4: Week of 2/12 Lecture 7: Introduction to Regression  Lecture 8: Regression for Predicting Housing Prices
5: Week of 2/19 Lecture 9: Regression for Predicting Housing Prices  Lecture 10: Regression for Predicting Housing Prices (In-class activities)

(Homework 2, Homework 1 DUE)

6: Week of 2/26 No Class – February Break Homework Review Q&A
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] (In-class activities)

(Homework 3, Homework 2 DUE)

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 (In-class activities)

(Homework 4, Homework 3 DUE)

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 (In-class activities)
13: Week of 4/15 Lecture 21: Final Project Discussion  Guest Lecture – FP Working Day (Homework 4 DUE)
14: Week of 4/22 Guest Lecture- Tariq Iqbal (UVA) Guest Lecture – Kilian Weinberger

FP Proposal DUE Friday, April 26th

15: Week of 4/29 Guest Lecture – Karen Levy 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
*Homework (HW)
*Final Project (FP)