{"id":14977138,"url":"https://github.com/rishitabansal9/loan-approval-predictor","last_synced_at":"2026-02-05T21:01:34.989Z","repository":{"id":209005795,"uuid":"722998393","full_name":"Rishitabansal9/Loan-Approval-Predictor","owner":"Rishitabansal9","description":"The project aims to predict loan approvals based on various factors, leveraging machine learning models and data pipelines. 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It encompasses an end-to-end machine learning pipeline, exploratory data analysis (EDA) notebooks, and code for model deployment on the Render platform.\n\n## Dataset\n\nThis  data set has 207 rows and 15 columns. \nKey Features:\n- Demographics: Age, Gender, State, and City provide a snapshot of the applicant's background.\n- Financial Information: Income, Credit Score, and Credit History Length offer insights into the applicant's financial stability and credit behavior.\n- Loan Details: The dataset sheds light on the specifics of the loan the applicant is seeking, with details like Loan Amount, Loan Tenure, and Loan to Value (LTV) Ratio.\n- Employment Information: The dataset includes both a general employment profile (e.g., Salaried, Self-Employed) and a specific occupation, giving a nuanced view of the applicant's employment status.\n- Profile Score: A composite score, ranging from 0 to 100, represents the overall credit profile of the applicant. This score can serve as a quick reference for gauging the creditworthiness of an individual. \n\n## Structure\n```\nLoan-Approval_Predictor/\n│\n├── artifacts/\n│   ├── data.csv\n│   ├── model.pkl\n│   ├── preprocessor.pkl\n│   ├── train.csv\n│   └── test.csv\n│\n├── notebook/\n│   ├── data/\n│   │   └── credit_data.csv\n│   └── Loan_approval.ipynb\n│\n├── src/\n│   ├── components/\n│   │   ├── __init__.py\n│   │   ├── data_ingestion.py\n│   │   ├── data_transformation.py\n│   │   └── model_trainer.py\n│   ├── pipeline/\n│   │   ├── __init__.py\n│   │   ├── predict_pipeline.py\n│   │   └── train_pipeline.py\n│   ├── __init__.py\n│   ├── exception.py\n│   ├── logger.py\n│   └── utils.py\n|\n├── static/\n│   └── style.css\n|\n├── templates/\n│   └── index.html\n|\n├── .gitignore\n|\n├── README.md\n|\n├── app.py\n|\n├── requirements.txt\n|\n└── setup.py\n```\n\n\n\n\n### 🏠 [Homepage](https://github.com/Rishitabansal9/Loan-Approval-Predictor/blob/main/README.md)\n\n### ✨ [Demo](https://loan-approval-predictor-es8r.onrender.com/)\n\n## Install\n\n```sh\nnpm install\n```\n\n## Usage\n\n```sh\n1. Clone the repository:\n   git clone https://github.com/YourUsername/Loan-Approval-Predictor.git\n   cd Loan-Approval-Predictor\n2. Install dependencies:\n   pip install -r requirements.txt\n3. Run:\n  python app.py\n```\n\n## Author\n\n👤 **Rishita Bansal**\n\n* Github: [@Rishitabansal9](https://github.com/Rishitabansal9)\n* LinkedIn: [@rishita-bansal-589056143](https://linkedin.com/in/rishita-bansal-589056143)\n\n## Show your support\n\nGive a ⭐️ if this project helped you!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frishitabansal9%2Floan-approval-predictor","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frishitabansal9%2Floan-approval-predictor","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frishitabansal9%2Floan-approval-predictor/lists"}