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Assignments

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:

Reading Assignments

Reading Assignment 1: Chapter 2 End-to-End of “Machine Géron, Aurélien. Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow.” O’Reilly Media, Inc., 2022. (Available on Canvas->Library Reserves)

  • Reading Quiz 1 Assigned: 1/26/2023 @ 5PM on Canvas
  • Reading Quiz 1 DUE: 2/2/2023 @ 5PM

 

Reading Assignment 2: Chapter 4 Training Models of “Machine Géron, Aurélien. Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow.” O’Reilly Media, Inc., 2022. (Available on Canvas->Library Reserves)

  • Reading Quiz 2 Assigned: 2/13/2023 @ 5PM on Canvas
  • Reading Quiz 2 DUE: 2/20/2023 @ 5PM

 

Reading Assignment 3: Chapter 3 Classification of “Machine Géron, Aurélien. Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow.” O’Reilly Media, Inc., 2022. (Available on Canvas->Library Reserves)

  • Reading Quiz 3 Assigned: 2/20/2023 @ 5PM on Canvas
  • Reading Quiz 3 DUE: 3/6/2023 @ 5PM

 

Reading Assignment 4: Chapter 9 Unsupervised Learning Techniques of “Machine Géron, Aurélien. Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow.” O’Reilly Media, Inc., 2022. (Available on Canvas->Library Reserves)

  • Reading Quiz 4 Assigned: 3/13/2023 @ 5PM on Canvas
  • Reading Quiz 4 DUE: 3/120/2023 @ 5PM

 

Reading Assignment 5: Chapter 14 Deep Computer Vision Using Convolutional Neural Networks of “Machine Géron, Aurélien. Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow.” O’Reilly Media, Inc., 2022. (Available on Canvas->Library Reserves)

  • Reading Quiz 5 Assigned: 3/27/2023 @ 5PM on Canvas
  • Reading Quiz  5 DUE: 4/10/2023 @ 5PM

 

Programming Assignments

Homework 1: Building End-to-End ML Pipeline & Dataset Curation. The goal of Homework 1 assignment is to build your first end-to-end Machine Learning (ML) pipeline using public datasets and by creating your own datasets. The learning outcomes for this assignment are [Github]: 

  • Build framework for end-to-end ML pipeline in Streamlit. Create your first web application! 
  • Develop web application that walks users through steps of ML pipeline starting with data visualization and preprocessing steps. 

Assigned: 2/3/2023 @ 5PM on Canvas and GitHub; Submission link: https://classroom.github.com/a/fiL30jIe

DUE: 2/17/2023 @ 11PM on Github; push changes to your local copy of the repository.

 

Deadlines

  • Reading Quizzes: Covers course topics in reading assignments and will be made available before after discussed in class.
  • Homeworks: Coding assignments on course topics, assigned on Wednesday and the following Wednesday @ 12PM
  • Final Project Proposal: Propose an FP on a PAML; DUE on April 28th @ 5PM. 
  • Final Project Midpoint Report: Provide updates on project deliverables on May 3th during the class session. 
  • Final Project Presentation: Present FP in class for 15 minutes with a 3-minute Q&A; scheduled on May 15th @ 12PM.
  • Final Project Report: Submit FP report; DUE on May 17th @ 12PM

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 (Tentative)

Week #
Lecture (M)
Lecture (W)
1: Week of 1/23
Introduction to PAML
  • HW0 Assigned; DUE on 2/6
  • Reading Assignment 0: Introduction to Machine Learning (Recommended, No DUE Date)
  • Reading Assignment 1: Building an End-to-End ML Pipeline
Revisit Preliminaries; In-class activity [Github]
Reading Quiz 1 Assigned on Thursday; DUE on 2/2 @ 12PM
2: Week of 1/30
Building an End-to-End ML Pipeline I
Building an End-to-End ML Pipeline II
  • Reading Quiz 1 DUE on 2/2 @ 5PM
  • HW1 Assigned on 2/3/2023; DUE on 2/17 @ 5PM [Github]
3: Week of 2/6
Dataset Creation, Acquisition, and Handling
  • Reading Assignment 2: Introduction to Regression
Dataset Creation, Acquisition, and Handling
4: Week of 2/13
Introduction to Regression I
  • Reading Quiz 2 Assigned; DUE on 2/13
  • HW2 Assigned; DUE on 2/20
Introduction to Regression II 
5: Week of 2/20
Regression for Predicting Housing Prices I
Regression for Predicting Housing Prices II
6: Week of 2/27
No Class – February Break
Scaling to Large Datasets
7: Week of 3/6
Introduction to Classification I
  • Reading Assignment 3: Introduction to Classification
  • Reading Quiz 3 Assigned; DUE on 3/13 
  • HW3 Assigned; DUE on 3/20
Introduction to Classification II
8: Week of 3/13
Classification for Product Recommendation I
  • Reading Assignment 4: Introduction to Clustering
Classification for Product Recommendation II
9: Week of 3/20
Introduction to Clustering I
  • Reading Quiz 4 Assigned; DUE on 3/27
  • HW4 Assigned; DUE on 4/10
Introduction to Clustering II
10: Week of 3/27
Clustering for Document Retrieval I
  • Reading Assignment 5: Introduction to Deep Learning
Clustering for Document Retrieval II
11: Week of 4/3
No Class – Spring Break
No Class – Spring Break
12: Week of 4/10
Deep Learning Fundamentals I
  • Reading Quiz 5 Assigned; DUE on 2/8
  • HW5 Assigned; DUE on 4/24
Deep Learning for Image Search II
13: Week of 4/17
Deep Learning for Image Search II
Final Project Discussion
14: Week of 4/24
FP Working Day
Guest Lecture – Tariq Iqbal (UVA)
15: Week of 5/1
FP Working Day
FP Working Day/Final Project Midpoint Report
16: Week of 5/8
Last Day of Instruction
No Class
17: Week of 5/15
Final Project Presentation
Final Project Report & Code Due
*Homework (HW)
*Final Project (FP)