When2Meet Autofiller

I developed a research paper to address the growing mental health crisis among high school students, through tackling two main issues: the lack of data correlating potential causes of mental health issues with students' emotional well-being, and the absence of tools to help educators identify students in need of support. To address this, I created a machine learning model that predicts students' mental health based on survey data about stressors. Through this project, I learned to work with large amounts of data with numpy and pandas and how to visualize models with seaborn. Additionally, I learned the basics of machine learning and utilized a neural network as well as linear regression in my project. Other code libraries that were used include tensorflow and sklearn.

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