Machine learning project to classify student scholarship eligibility based on academic and social factors.
This project uses machine learning to classify students as Eligible or Not Eligible for scholarships based on academic performance and social background.
- Predict scholarship eligibility
- Apply classification algorithms
- Understand real-world decision-making systems
- GPA → Academic performance
- Orphanage → Whether student is orphaned
- Disability → Whether student has a disability
- Other social and academic indicators
- Data preprocessing and cleaning
- Exploratory Data Analysis (EDA)
- Model building using classification algorithms
- Model evaluation using accuracy, recall, and F1-score
- Random Forest Classifier
- Model predicts student eligibility effectively
- Key factors include GPA and social conditions
- Dataset may be limited
- Model needs updates with new data
- No real-time system implemented
- Open the Jupyter Notebook
- Run all cells step by step
- Python
- Pandas
- Scikit-learn
- Matplotlib / Seaborn
- Jupyter Notebook
MUHIYADIN2025