Dropout vs Success

This repository contains the core components of the project focused on predicting Dropouts and Success rates based on several factors.

Repository Contents

• Notebook/ — Main analysis and modeling workflow
• Data/ — Contains the raw csv used in the making of this project
• App/ — Contains the training data and model specifications.

Technologies Used

• Python (Pandas, NumPy, Scikit-learn, Seaborn)
• Jupyter
• Streamlit

Project Highlights

• End-to-end data science workflow
• Modular and reproducible code
• Deployed solution demonstrating practical application

Deployment

A live version of the project is available here.

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