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:
Deadlines
 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 3minute 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 EndtoEnd ML Pipeline  Lecture 4: Dataset Curation (Homework 0 DUE) 
3: Week of 2/5  Lecture 5: Preprocessing I

Lecture 6: Preprocessing II (Inclass 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 (Inclass 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] (Inclass 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 (Inclass 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 (Inclass 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 