DSC 340: Machine Learning and Neural Network Processing Final Project

Instead of a final exam, in this class, you will submit a final project consisting of two parts: a presentation that will be given during the last week of the course and a final paper due on the last day of the course.


This project can be completed individually or in groups of up to three people. If you choose to work in a group for this project, each person must contribute equally. Appendix B in the textbook Hands-On Machine Learning by Aurélien Géron has a thorough list of the steps that need to be taken to complete a machine learning project from start to finish.

Warning: This project cannot be completed the night before it is due. Instead, you are expected to work on this project for an hour or two every week. In addition, most of the post-class homework assignments will ask you to submit something relating to your final project. Sometimes this will be a component of the report or presentation, and sometimes just a brief (one-paragraph) update on how the project is progressing.

Final Project Topics

For this project, you must create a question you want to answer using machine learning. This could be analyzing a particular data set, building an image classifier, investigating reinforcement learning, or any other aspect of machine learning you find interesting. The project chosen must have sufficient length and complexity for both the final presentation and report and be different from work already done. You can draw inspiration from work you find online, but the project you submit must be original work.

The topic you choose for your final project could be based on something you find interesting from an academic standpoint (astronomy or ecology data sets, for example) or something you are interested in from hobbies or other aspects of your personal life (sports data or housing prices, for example). You will spend a reasonable amount of time on this project throughout the semester, so choosing a topic you are interested in will keep you motivated and make working on this project easier.

Final Presentation Guidelines

You will present your project to your classmates during the last week of class in a 10-minute presentation. You should explain the problem you are trying to solve, how you applied machine learning to solve it, your results, and an analysis of the results. You can use Powerpoint slides or a Python notebook as visuals to help with your presentation. Everyone must present some part of the work if you are working in a group for this project. The class will have two minutes after the presentation to ask the presenter questions about their work.

Submitting Code for Final Project

You must submit the code you used to analyze this project through D2L before the final class of the semester. The code does not have to be perfect, but you should attempt to use the best coding practices while creating it, and the code should be original to the fullest extent possible.

Final Paper Guidelines

Final Project Deadlines

Data set and problem statement (DUE: September 8, 2023 BEFORE the start of class)

The problem statement should be ~one paragraph describing what data set you plan on using for this project and what problem you are trying to solve that arises from the data set.

Project analysis (DUE: September 22, 2023 BEFORE the start of class)

Your project analysis should be an approximately one-page document explaining what machine learning method you plan on using, how that method can be used to solve your proposed problem, how is your work different from similar work that has already been done, and what potential problems you foresee occurring as you are working on this project.

Abstract (DUE: October 27, 2023 BEFORE the start of class)

This will be abstract to your final report as described in the paper guidelines section. However, since you will not have your final results yet, you can instead describe any initial results you have gotten or what results you intend to have before you submit your final project. These will be collected into one document and released to the class so everyone can see what will be presented during the final week of class.

Introduction to report (DUE: November 10,2023 BEFORE the start of class)

You will submit the introduction section to your final report using the description in the paper guidelines section above. This is to give you an idea of whether your writing is sufficient for the final paper. The introduction draft you submit here does not have to be the final version of your paper.

Results graph (DUE: November 21, 2023 BEFORE 5pm)

You must submit one graph from the results section of your final project. It can be any graph you want, but it must be well formatted and convey the data it presents.

Presentation, report, and final code (DUE: December 4, 2023 BEFORE the start of class)

Your presentation, report, and final code need to be upload to D2L before the start of class on December 4.  You will be given a presentation time during the week of December 4 to present your work to the class.

Final Project Grading

The final project will be a total of 100 grade points that you can earn and will be divided into the following categories:

If any of the work you submit is found to be plagiarized or not original, you will receive an automatic zero for the project.

Project Examples and Inspiration