Introduction to Machine Learning

Overview

The goal of this project is for you to develop your skills in conducting and communicating original research. Interested students will be supported (and encouraged) by the instructor to submit this semester-long project for publication or as part of your application to find an exciting job opportunity in industry.

For your project, you will design and investigate a novel idea involving machine learning. It will be a self-designed project in consultation with the instructor. The only requirement is it includes a machine learning component with analysis. This is an opportunity for you to enhance your expertise on a topic you feel passionate about.

Your final project will constitute 40% of your total class grade. Your project grade will be calculated as follows:

Assignment Percentage of Final Project Grade Due
Project pre-proposal 5% March 27 at 11:59pm CDT
Project proposal 10% April 3 at 11:59pm CDT
Project outline submission 20% April 17 at 11:59pm CDT
Final project presentation 10% May 2 during class
Peer evaluation 10% May 2 by the end of class
Final project submission 45% May 9 at 11:59pm CDT
iSchool Open House Presentation Optional May 4 at 1-4pm

Project Pre-proposal

The project pre-proposal should establish:

After submitting your ideas, you will need to choose a 10 minute time slot that works for all group members to meet with the instructor to discuss the ideas. Available time slots will be posted.

When choosing your topic, general guidelines are to:

  • Choose a problem you have an idea for how to solve
  • Choose a problem someone else cares about
  • Choose a problem that is not yet solved (know current literature!)
  • Choose a problem that you can objectively evaluate by tying it to a task
  • Revisit advice on how to read a research paper to evaluate your own ideas (e.g,. from the first week of assigned readings)
  • Project Proposal

    The project proposal should:

    1. Establish the research problem and novel idea your group will tackle for your course project.
    2. Identify relevant related work.
    You will need to submit one PDF per group that is 1-2 pages long (excluding references). The paper should include each of the following:

    Please note that your proposed project is not a binding contract. You will continue to update and improve it as you learn more from your readings and/or feedback.

    Project Outline Submission

    The project outline should map out the entire project. You will be expected to:

    1. Submit a detailed project outline that is 4-6 pages long (including references).
    2. Demo your proposed machine learning system; you should have a complete working prototype that you will use for your experiments.
    You will need to choose a 10 minute time slot that works for all group members to meet with the instructor to demo the system and receive feedback on the paper. Available time slots will be posted before the due date.

    For the project outline, you should submit one PDF per group. The paper should include each of the following:

    Final Project Presentation

    The final project presentation will involve:

    1. Presenting a 5 minute recorded video about your project.
    2. Taking 5 minutes to answer questions from the audience.
    Your video should be no longer than 5 minutes and should do the following: Please design your video for an audience who has not taken the class. In other words, your mom, dad, friend, or a potential employer should be able to watch it and understand what you did and why what you did is valuable.

    At the end of class, a best project award will be announced. The best paper will be determined by popular vote from the members of the class.

    Indicate in your submission on Canvas whether you are submitting a video in .mp4 format, a public URL for your video, or a video generated with Panopto. If you are submitting a .mp4 video, then email that to me the video at danna.gurari@ischool.utexas.edu. If you are submitting a public URL, then indicate this URL in your Canvas submission. For Panopto videos, you do not need to do anything extra.

    Peer Evaluation

    You will evaluate the presentation from every group (including your own) as the video is presented on paper surveys that will be collected at the end of class. The evaluations will not take time outside of class. The evaluations that you do for other students' projects will not affect your own grade, except that you will be penalized if you do not complete an evaluation for every group.

    Final Project Submission

    For the final project submission, you should submit a zip file which contains the following content:

    The paper should include each of the following:

  • Title
  • Abstract - one paragraph summary of your paper describing the motivation, problem, conducted experiments, and experimental findings
  • [Section 1] Introduction (improve upon the material from your project outline)
  • [Section 2] Related Work (improve upon the material from your project outline; if you have not already, you should remove the bulleted structure you used in the initial proposal and instead have a paragraph form)
  • [Section 3] Methods (improve upon the material from your project outline)
  • [Section 4] Experimental Design (improve upon the material from your project outline)
  • [Section 5] Experimental Results (improve upon the material from your project outline)
  • [Section 6] Conclusions (improve upon the material from your project outline)
  • [Section 7] Bibliography
  • iSchool Open House Presentation