🎓 Admission Probability Predictor using Linear Regression

This project predicts the chance of admission to a university based on academic and personal profile features using linear regression.

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📊 Project Overview

The dataset contains information about student profiles (GRE, TOEFL, CGPA, SOP, LOR, etc.). This project:

• Trains a linear regression model to predict the Chance of Admit
• Evaluates model performance
• Accepts user input to predict admission chances interactively

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🛠️ Technologies Used

• Python
• Pandas
• Scikit-learn

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🧪 Features

• Cleaned dataset from YBI Foundation
• Interactive prediction after training
• Evaluation using MAE, MAPE, MSE
• Simple, beginner-friendly code

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🚀 How to Run

• git clone https://github.com/nikgarhwal/admission_probability.git

• cd admission_probability

• pip install -r requirements.txt

• python admission_predictor.py

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📸 Sample Output

• 📊 Model Evaluation:
  • MAE: 0.0431
  • MAPE: 7.40%
  • MSE: 0.0039

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##🎓 Predict Your Admission Probability

• Enter GRE Score: 320
• Enter TOEFL Score: 110 ...
• 🧾 Estimated Chance of Admission: 81.25%

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📄 License

This project is licensed under the MIT License.