https://github.com/firaskahlaoui/loan-prediction

Comprehensive learning exercise covering data cleaning, visualization, interpreting results, model building, and interface development using Flask.
https://github.com/firaskahlaoui/loan-prediction

flask-application jupyter-notebook kaggle-dataset learning-by-doing

Last synced: about 5 hours ago
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Comprehensive learning exercise covering data cleaning, visualization, interpreting results, model building, and interface development using Flask.

• Host: GitHub
• URL: https://github.com/firaskahlaoui/loan-prediction
• Owner: FirasKahlaoui
• Created: 2024-05-20T07:57:00.000Z (6 months ago)
• Default Branch: master
• Last Pushed: 2024-06-23T22:07:21.000Z (5 months ago)
• Last Synced: 2024-06-23T23:23:01.389Z (5 months ago)
• Topics: flask-application, jupyter-notebook, kaggle-dataset, learning-by-doing
• Language: Jupyter Notebook
• Homepage:
• Size: 163 KB
• Stars: 11
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Loan Prediction Project

## About This Project

The "loan-prediction" project is a comprehensive learning exercise covering data cleaning, visualization, interpreting results, model building, and interface development using Flask. It aims to predict loan approval status based on various features and provide insights into the data analysis process.

### Features

- **Data Cleaning**: Preprocessing the loan dataset to handle missing values, outliers, and data transformations.

- **Exploratory Data Analysis (EDA)**: Visualizing data distributions, correlations, and insights using Python libraries like Pandas, Matplotlib, and Seaborn.

- **Model Building**: Developing machine learning models (e.g., logistic regression, decision trees) to predict loan approval.

- **Model Evaluation**: Evaluating model performance using metrics like accuracy, precision, recall, and ROC curves.

- **Interface Development**: Building a web interface using Flask to interactively predict loan approval based on user inputs.

## Technologies Used

- Python

- Pandas, NumPy for data manipulation

- Matplotlib, Seaborn for data visualization

- Scikit-learn for machine learning model building and evaluation

- Flask for web interface development

## Installation

1. Clone the repository:

   ```bash

   git clone https://github.com/FirasKahlaoui/loan-prediction.git

   cd loan-prediction