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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.