Student_Success_Prediction

🎓 Student Success Prediction

An end-to-end Machine Learning web application that predicts a student's final score and success metrics based on various academic and behavioral features. This project is deployed on Hugging Face Spaces using Streamlit.

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🚀 Features

• Accurate Predictions: Utilizes a trained machine learning regression pipeline.
• Interactive UI: Built with Streamlit for a smooth and user-friendly experience.
• Robust Preprocessing: Uses serialized scaling and column transformation to ensure data consistency.

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📁 Repository Structure

• app.py: The main Streamlit application file handling user inputs and UI.
• model.pickle: The trained Machine Learning model serialized using Pickle.
• scale.pickle: The serialized StandardScaler instance used for feature scaling.
• column.pickle: The serialized column transformer or list of feature columns to maintain structural alignment.
• README.md: Model documentation and instructions.

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🛠️ How It Works

1. User Input: The user provides student details (e.g., study hours, attendance, previous grades) via the Streamlit frontend.
2. Data Transformation: column.pickle aligns the features, and scale.pickle scales the numerical data to match the training distribution.
3. Inference: The processed data is fed into model.pickle to predict the final student score instantly.

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💻 Local Installation & Setup

If you want to run this project locally, follow these steps:

1. Clone the repository:

   git clone [https://huggingface.co/spaces/amirsoahil101/Student_Success_Prediction](https://huggingface.co/spaces/amirsoahil101/Student_Success_Prediction)