📄 AI Based Resume Screening App

🔍 Overview

The Resume Screening App is a machine-learning-powered tool that classifies resumes into different job categories based on their content. The application utilizes Natural Language Processing (NLP) techniques and a trained Logistic Regression and Random Forest model to make predictions.

Demo

Try it out at - Link

🚀 Features

• 📂 Upload a resume (Text/PDF/DOCX)
• 🔍 Extract key details (Name, Contact, Education, Skills, Education Detalis)
• 🎯 Predict the job category
• 📊 Interactive Streamlit UI for real-time predictions

🏗️ Tech Stack

• Python 🐍
• Streamlit (Web UI)
• Scikit-learn (ML models)
• NLTK & SpaCy (Text Processing)
• Pandas & NumPy (Data Handling)
• Pickle (Model Storage)

📂 Directory Structure

└── arpitkadam-resume-screening-app/
    ├── Resume_Categorization.ipynb   # Notebook for training and testing models
    ├── main.py                        # Streamlit web app
    ├── requirements.txt               # Dependencies
    ├── data/
    │   └── clean_resume_data.csv       # Preprocessed resume dataset
    ├── images/                         # UI and result snapshots (optional)
    ├── models/
    │   ├── best_LogisticRegression_model.pkl  # Logistic Regression Model
    │   ├── best_RandomForest_model.pkl        # Random Forest Model
    │   └── vectorizer.pkl                      # TF-IDF Vectorizer
    └── .streamlit/
        └── config.toml                         # Streamlit configurations

⚡ Installation & Usage

🔹 1. Clone the Repository

git clone https://github.com/ArpitKadam/Resume-Screening-App.git
cd Resume-Screening-App

🔹 2. Create a Virtual Environment (Optional but Recommended)

python -m venv venv
source venv/bin/activate  # For Mac/Linux
venv\Scripts\activate     # For Windows

🔹 3. Install Dependencies

pip install -r requirements.txt

🔹 4. Run the Application

streamlit run main.py

🖼️ Screenshots

📊 Countplot of Job Categories

📊 Pieplot of Job Categories

🏆 Models Used

• Logistic Regression ✅
• Random Forest Classifier 🌳
• TF-IDF Vectorizer for feature extraction ✨

✨ Features Implemented

✔️ Resume Text Processing (Name, Email, Contact, Skills, Education, Education Details.) ✔️ Job Category Prediction ✔️ Interactive Streamlit UI ✔️ Pretrained ML Models for Accuracy

🤝 Contributing

Pull requests are welcome! Feel free to open an issue for discussions.

📜 License

This project is open-source under the MIT License.

🔗 Connect with Me

🚀 Happy Coding! 🎯