🏠 Loan Prediction with Machine Learning

Welcome to the Loan Prediction repository! This project uses machine learning to predict loan approval based on applicant data. The analysis is conducted using Python, with the main work done in a Jupyter Notebook.

📖 Introduction

Loan approval prediction is a critical task in the finance industry. This project aims to build a predictive model that helps banks and financial institutions assess the likelihood of a loan being approved based on various applicant features.

✨ Features

• Data Preprocessing: Clean and preprocess the loan application dataset to ensure accurate model predictions.
• Machine Learning Models: Implement various classification algorithms to predict loan approval status.
• Performance Evaluation: Evaluate model performance using metrics like accuracy, precision, recall, and F1-score.
• Visualization: Visualize important trends and insights from the data to support decision-making.

📊 Dataset Information

The analysis is based on the Loan Prediction Dataset provided in this repository. The dataset includes features like applicant income, loan amount, credit history, and more.

Important:

• Dataset Files:
  • train_u6lujuX_CVtuZ9i.csv: Training data used to build the model.
  • test_Y3wMUE5_7gLdaTN.csv: Test data used to evaluate the model.

🛠️ Installation Instructions

1. Clone the repository:

   git clone https://github.com/yajasarora/Loan-Prediction.git
   cd Loan-Prediction

2. Install the required dependencies: Ensure you have Python 3.x installed. Then, install the necessary packages:

   pip install -r requirements.txt

3. Run the Jupyter Notebook: Open the Jupyter Notebook main.ipynb to explore the analysis:

   jupyter notebook main.ipynb

🚀 Usage

• Data Exploration: Explore the dataset in the notebook to understand the features and relationships.
• Model Training: Follow the steps in the notebook to preprocess the data and train the machine learning models.
• Prediction: Use the trained models to predict loan approval on the test data and evaluate the performance.

📈 Results and Visuals

Here are some key insights and visualizations generated by the analysis:

• Feature Importance Analysis: [Visualization Placeholder]
• Loan Approval Prediction Results: [Visualization Placeholder]

🤝 Contributions

Contributions to this project are welcome! If you have ideas for improving the prediction accuracy or adding new features, feel free to fork the repository and submit a pull request.

📬 Contact

For any questions or feedback, feel free to reach out via GitHub Issues or contact me directly.

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Predict loan approvals with confidence using data-driven insights! 🏠