This project aims to predict the likelihood of students being accepted into specific colleges based on various factors. By leveraging machine learning algorithms, we can provide valuable insights to both students and educational institutions
The dataset used for this project includes the following features:
- GRE Score , TOEFL Score
- SOP, LOR and CGPA
- Chance of admit (percentage of getting admission)
- Other Relevant Factors (e.g., extracurricular activities, personal statements)
- Clone this repository
- Install the necessary dependencies (e.g., scikit-learn, pandas, Jupyter Notebook).
- Explore the Jupyter Notebook files to understand the models and their implementation.
- Input student data (GRE Score , TOEFL Score,Chance of admit, etc.) to make predictions