info1998-final

This project analyzes and predicts major depressive disorder (MDD) among students using a dataset of student mental health indicators. The notebook includes data cleaning, visualization, and machine learning models (Logistic Regression and Random Forest) to identify key contributors to depression.

How to Run

1. Clone or download this repository and ensure you have the dataset file student_depression_dataset.csv in the same directory as the notebook.
2. Open info1998.ipynb in Jupyter Notebook, VS Code, or Google Colab.
3. Before running the notebook, make sure you have all the required Python packages installed.

Dependencies

• pandas
• scikit-learn
• matplotlib
• seaborn

You can install all dependencies with:

pip install scikit-learn pandas matplotlib seaborn

Project Structure

• info1998.ipynb — Main analysis and modeling notebook
• student_depression_dataset.csv — Dataset file
• README.md — Project overview and instructions

Authors

Nicole Luo, Anna Sahakyan, Andelo Vrdoljak