The Resume Shortlisting Predictor is a machine learning-based Streamlit web app that analyzes resumes and predicts whether they are likely to be shortlisted.
It allows users to upload their resume or paste the text for instant predictions, helping job seekers optimize their resumes for better chances.
- Resume Upload – Upload
.txt,.docx, or.pdfresumes for analysis. - Text Input – Paste your resume text directly into the app.
- Machine Learning Predictions – Uses a trained ML model to classify resumes as Shortlisted or Rejected.
- Beautiful UI – Custom gradient background, styled upload box, and clean typography.
- Fast & Easy – Instant predictions with just a click.
- Frontend & Deployment: Streamlit
- Backend & ML: Python, scikit-learn, pandas, numpy, matplotlib, seaborn
- File Handling: joblib, nltk, pickle
- Styling: Custom CSS for Streamlit
Resume-Shortlisting-Predictor/
│
├── app.py
│ Main Streamlit application
│
├── model/
│ ├── clf.pkl → Trained classification model
│ ├── tfidf.pkl → TF-IDF vectorizer
│ ├── encoder.pkl → Label encoder
│
├── utils/
│ ├── preprocessing.py → Functions for text cleaning and preprocessing
│ ├── prediction.py → Model loading and prediction functions
│
├── assets/
│ ├── style.css → Custom CSS styling for Streamlit app
│
├── data/
│ └── sample_resume.txt → Example resume text for testing
│
├── screenshots/
│ └── app_preview.png → Screenshot for README
│
├── requirements.txt → Python dependencies
├── README.md → Project documentation
└── LICENSE → License file
This project is licensed under the Apache 2.0 – you are free to use and modify it.
Special thanks to open-source communities and Python libraries that made this project possible.