π Student Placement Prediction
A Machine Learning web application that predicts whether a student is likely to get placed based on academic and skill-based attributes.
π Features
- Student placement prediction
- Random Forest Classifier
- Interactive Gradio web interface
- Probability score
- Easy deployment on Hugging Face Spaces
π οΈ Technologies Used
- Python
- Pandas
- NumPy
- Scikit-learn
- Gradio
- Joblib
π Project Structure
placement_project/
β
βββ app.py
βββ train_model.py
βββ requirements.txt
βββ README.md
βββ .gitignore
β
βββ dataset/
βββ model/
βββ notebooks/
βββ screenshots/
βΆοΈ Run Locally
Install dependencies:
pip install -r requirements.txt
Run:
python app.py
π Machine Learning
- Algorithm: Random Forest Classifier
- Data Preprocessing:
- Missing value handling
- One-Hot Encoding
- StandardScaler
- Evaluation:
- Accuracy
- Classification Report
- Confusion Matrix
π¨βπ» Author
Ravi Kandoriya
Inference Providers NEW
This model isn't deployed by any Inference Provider. π Ask for provider support