Credit-Card-Fraud-Detection

Machine Learning-based Credit Card Fraud Detection System using Random Forest, FastAPI, and Streamlit for real-time fraud prediction.

Credit Card Fraud Detection System

A complete End-to-End Machine Learning project that detects fraudulent credit card transactions in real-time.

Tech Stack

• Language: Python 3.12
• ML Framework: Scikit-Learn, RandomForestClassifier
• Development Environment: Jupyter Notebook, VS Code, Git

Project Overview

This project focuses on building a robust system to identify fraudulent transactions. It involves data exploration, feature engineering, and training a machine learning model to classify transactions as 'Fraud' or 'Normal' with high accuracy.

Features

• Data Analysis: Extensive data exploration and feature engineering performed in the Jupyter notebook.
• Model Training: Utilizes Random Forest for efficient fraud classification.
• Pipeline Setup: Structured approach for model training and evaluation.