Bank Loan Prediction System
These days, with everything being data-based, predicting if someone can get a loan or not can really help banks work faster. This Bank Loan Prediction System is made using Streamlit and gives you a live, interactive web app that runs with machine learning models trained on past data.The project is made in a clean, pro way and it’s actually a paid one. It’s great for students, devs, or even companies who wanna learn about loan prediction or actually use it in real life.
Project Overview
This system predicts whether a loan should be approved based on several applicant details like income, credit history, marital status, employment, etc. Developed using Python and Streamlit, the application is powered by a pre-trained ML model and provides an interactive interface to submit applicant data and get predictions instantly.
Project Details
| Project Name | Bank Loan Prediction System using Streamlit |
|---|---|
| Language/s Used | Python 3.6 |
| Type | Web Application |
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Machine Learning and Data Processing
- Jupyter Notebook (
Str_Loan_ML.ipynb) - Cleaned and processed dataset files located in the
Loan_Data/folder - A pre-trained model stored in
Model/ML_Model.pklused by the main Streamlit app
Files Included in the Project
Bank_Loan_Prediction.py– Main Streamlit applicationStr_Loan_ML.ipynb– Jupyter notebook for preprocessing and model trainingrequirements.txt– Lists all required Python librariesLoan_Data/train.csvandLoan_Data/test.csv– Dataset used for training/testingModel/ML_Model.pkl– Trained Machine Learning model- Multiple screenshots and project preview images
Available Features
- User-friendly Web Interface using Streamlit
- Predicts loan approval eligibility
- Uses pre-trained machine learning model
- Clean and structured dataset included
- Easy to customize and retrain
- Includes complete Jupyter Notebook for data processing
- Professional UI with visual feedback
- Visual examples included for reference
Usage
- Clone the repository or download the complete ZIP.
- Install the required libraries using:
pip install -r requirements.txt - Run the Streamlit app using:
streamlit run Bank_Loan_Prediction.py
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