During this week I:

• completed a final machine learning assignment given to be my mentor. This assignment was about applying what I learned in the Machine Learning Mastery courses to predict if someone survived the Titanic based on given attributes about the person and their stay on the Titanic. The problem details and dataset are part of a Kaggle competition
• In Project 1: Suicide Prevention, assisted in the writing and scripts necessary for the next paper related to the project. In this paper, we will pair the suicidality prediction model with the LLaMA language generation model so that there are explanations for the predictions for a user. This paper will focus on prompt engineering, with how we tell LLaMA what the predicted level of risk is and guide it into an explanation for that prediction.

During this week I:

• In Project 1: Suicide Prevention, continued work on the documentation for the entire project.
• In Project 1, I met with my research mentor Dr. Nur and a student researcher to discuss a new paper idea he had that builds on what we previously worked on. After this meeting, I am set to become a project manager and paper writer for that paper this Fall.
• Worked on my DREU Final Report and feedback survey.

During this week I:

• Completed a mini-course on Machine Learning Mastery. The full title for this mini-course is “Weka Machine Learning (no code)”. I learned how to use the Weka tool to understand and improve machine learning algorithms with tools like feature selection.
• In Project 1: Suicide Prevention, had knowledge transfer meetings with the two primary student researchers so that I can write the documentation.
• In Project 1, began work on the documentation for the entire project.
• In Project 2: Math Education App, met with Victor to set up GitHub for his animations.

During this week I:

• In Project 3: Math Education App, continued writing the pre-survey concerning how high schoolers and college students think/thought about their ability to understand of their high school math education, and post-survey for specific feedback about particular animations and the app in general. See Victor’s site for more about the math app.
• Created blog posts for weeks 3-7
• Submitted the Progress Report with minor reformatting and editing.
• Divided the gathered related work for Project 1: Suicide Prevention’s conference paper into categories to assist in writing the Related Work section. This task was shared with Victor
• In Project 2: ADHD In The Workplace, used the Scholarcy tool to generate summaries for the previously gathered related work. The related work was gathered before the DREU program started. This task was shared with Victor.

During this week I:

• Wrote feedback for Victor’s math education app (Project 3) that provides animations to clarify math concepts. I gave feedback on 10 animations, and I did my best to reference the documentation of the Java library he was using, and catch every detail.
• Also in Project 3, Started writing the pre-survey concerning how high schoolers and college students think/thinked about their ability to understand of their high school math education, and post-survey for specific feedback about particular animations and the app in general.

During this week I:

• Used the Scholarcy tool to generate summaries for the previously gathered related work for Project 1: Suicide Prevention. I completed the remaining half of the summaries left from last week.
• Completed my DREU Progress Report. I would have submitted this week, but the option to submit wasn’t available.

During this week I:

• Used the Scholarcy tool to generate summaries for the previously gathered related work for Project 1: Suicide Prevention. I completed only half of the summaries this week.
• completed the second of two recommended mini-courses on Machine Learning Mastery. The full title for this mini-course is “Python Machine Learning”. The other relevant course will be completed next week. In this mini course, I learned how to:
  • use debugging tools on Python code.
  • Profile Python code in terms of time to execute with the pstats, cProfile, and time modules.
  • Visualizing data into 2D and 3D plots with Bokeh, Seaborn, and Matplotlib
  • Obtain time series datasets (a collection of data pulled at constant intervals in time) using the pandas_datareader library. The library supports gathering data from commonly used sources on the web like Yahoo Finance.

During this week I:

• Reviewed the “Python Machine Learning (scikit-learn)” course I completed last week to ensure I knew everything I needed to.
• Created a presentation detailing what I learned from the course last week.
• Got my DREU website up with posts for the first 2 weeks. I met with Victor for help because he has experience with web development.
• Gathered related work from Google Scholar for Project 1: Suicide Prevention.

During this week I:

• Fixed my broken anaconda installation. The relevant anaconda-clean package wasn’t able to be installed because of issues with the base environment, so I learned about creating new environments.
• Completed the first of two recommended mini-courses on Machine Learning Mastery. The full title for this mini-course is “Python Machine Learning (scikit-learn)”. The other relevant course will be completed later. In this mini course, I learned how to:
  • Create a pandas.DataFrame from a CSV and how to specify a header row (if it exists).
  • Use relevant pandas.DataFrame methods to get a peek of the data and a statistical summary per attribute of the data.
  • Use matplotlib to display statistical plots like histograms.
  • Use scikit-learn to create classification models of the data and evaluate their accuracy with visuals.
• Met with Victor, another DREU program participant under the same mentor, for him to teach me about the Weka tool for understanding machine learning models, and to give him an overview of the Suicide Prevention project so far. I am more knowledgeable about the project because I have been attending weekly meetings since the start of the Spring 2023 semester.
• Finished the application to apply for funding to the 2023 Tapia Conference and 2023 Grace Hopper Conference. My mentor and I think these conferences can be great opportunities.
• Gathered related work on Google Scholar to be read and considered for use in the Suicide Prevention project paper to be submitted to a machine learning conference.

During this week I:

• Completed refresher exercises to re-familiarize myself where necessary with the Python language and relevant packages. I completed exercises at https://learnpython.org. The sections I completed were
  • Classes and Objects
  • Modules and Packages
  • NumPy Arrays
  • Pandas Basics
• Completed CITI ethical compliance training for research with human subjects.
• Started the application to apply for funding to the 2023 Tapia Conference and 2023 Grace Hopper Conference. My mentor and I think these conferences can be great opportunities.
• Used the Scholarcy Chrome extension to automatically generate summaries for the related work we have gathered for the Suicide Prevention project paper to be submitted to a 2023 conference.