This project is a machine learning-powered web application that predicts the job-fit category of uploaded resumes (PDFs) using natural language processing (NLP).
It’s built with:
- 🔍 Scikit-learn for training a resume classifier
- ⚡ FastAPI for creating a lightweight backend API
- 🎨 Streamlit for an interactive frontend UI
- 🐳 Docker for containerization
- 🌐 Render for live cloud deployment
- 🎨 Frontend UI: https://resume-streamlit-ui.onrender.com
- ⚙️ API Docs: https://resume-classifier-c1ub.onrender.com/docs
Upload a resume PDF and get an instant prediction of its best-fit job category.
- Upload PDF resumes
- Automatically extracts text using PyMuPDF
- Predicts the candidate's likely role:
Data Scientist,Web Developer,Business Analyst, etc.
- RESTful API served with FastAPI
- Interactive frontend built in Streamlit
| Layer | Tools |
|---|---|
| Machine Learning | Scikit-learn, TfidfVectorizer |
| Backend API | FastAPI, Uvicorn |
| PDF Parsing | PyMuPDF |
| Frontend UI | Streamlit |
| Deployment | Docker, Render |
resume-classifier/ ├── app/ # FastAPI backend ├── model/ # Saved ML model + vectorizer ├── streamlit-app/ # Streamlit frontend │ ├── app.py │ ├── requirements.txt │ └── Dockerfile ├── train_model.py # Model training script ├── requirements.txt ├── Dockerfile # For FastAPI backend └── README.md
# Install dependencies
pip install -r requirements.txt
# Train model
python train_model.py
# Run FastAPI
uvicorn app.main:app --reload
Open: http://localhost:8000/docs
Frontend (Streamlit)
cd streamlit-app
pip install -r requirements.txt
streamlit run app.py
Open: http://localhost:8501
📦 Docker Deployment (Optional)
Both frontend and backend are containerized.
# Build and run FastAPI
docker build -t resume-api .
docker run -p 8000:8000 resume-api
# Build and run Streamlit UI
cd streamlit-app
docker build -t resume-ui .
docker run -p 8501:8501 resume-ui👨💻 Author Abishek Ravichandiran Aspiring ML Engineer | CSE + Business Analytics
🔗 LinkedIn https://www.linkedin.com/in/abishek316/
📬 abishekravichandiran7@gmail.com
https://github.com/Abishek7952/
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