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Data Scientist\n  - Backend Developer\n  - Frontend Developer\n  - Full Stack Engineer\n  - DevOps Engineer  \n- Clean interactive UI powered by Streamlit\n\n---\n\n## 🛠 Tech Stack\n\n| Area         | Tools \u0026 Libraries                                           |\n|--------------|-------------------------------------------------------------|\n| Language     | Python                                                      |\n| ML/NLP       | `scikit-learn`, `pandas`, `joblib`, `TfidfVectorizer`       |\n| PDF Parsing  | `PyMuPDF` (`fitz`)                                          |\n| Web UI       | `Streamlit`                                                 |\n\n---\n\n## 📁 Folder Structure\n\n```bash\nHireSense/\n├── app.py                # Streamlit App\n├── requirements.txt      # Dependencies\n├── model/                # Trained ML model + vectorizer\n├── preprocess/           # Data processing scripts\n├── data/                 # labels.csv, resume texts\n├── .gitignore\n└── README.md\n\n---\n\n## How to Run Locally\n\n### 1. Install dependencies\n\n```bash\npip install -r requirements.txt\n````\n\n### 2. Run the Streamlit app\n\n```bash\nstreamlit run app.py\n```\n\n---\n\n##  How to Train Your Own Model\n\nIf you want to retrain the model using the Kaggle dataset:\n\n```bash\npython preprocess/convert_kaggle_dataset.py\npython model/train_model.py\n```\n\n* The first script converts the CSV into labeled text files.\n* The second script trains a logistic regression model and saves it as `.pkl`.\n\n````\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frohit-2301%2Fhiresense","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frohit-2301%2Fhiresense","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frohit-2301%2Fhiresense/lists"}