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This Python project uses Isolation Forest for credit card fraud detection, analyzing transaction data and visualizing distributions. It employs PyCaret for model comparison, highlighting Random Forest. The project is concise and effective for fraud detection.

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Shreyaprasad21/Credit-Card-Fraud-Detection

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Credit Card Fraud Detection

This repository contains code for detecting credit card fraud using machine learning techniques.

Files

  1. Credit_Card_Fraud_Detection.ipynb: Jupyter Notebook containing the code for credit card fraud detection.
  2. LICENSE: License information for the repository.
  3. README.md: This file; provides an overview of the repository.

Overview

The Credit_Card_Fraud_Detection.ipynb notebook includes:

  • Data preprocessing steps.
  • Feature engineering techniques.
  • Application of machine learning models (e.g., logistic regression, random forest) for fraud detection.
  • Evaluation metrics used to assess model performance.

Usage

To run the notebook:

  1. Clone the repository: https://github.com/Shreyaprasad21/Credit-Card-Fraud-Detection.git
  2. Navigate to the directory: cd Credit-Card-Fraud-Detection
  3. Install dependencies if necessary.
  4. Open and run the Credit_Card_Fraud_Detection.ipynb using Jupyter Notebook or JupyterLab.

License

This project is licensed under the MIT License.

About

This Python project uses Isolation Forest for credit card fraud detection, analyzing transaction data and visualizing distributions. It employs PyCaret for model comparison, highlighting Random Forest. The project is concise and effective for fraud detection.

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