Welcome to the Credit Card Fraud Detection System project! This machine learning project is designed to identify and flag potential fraudulent credit card transactions. By utilizing advanced data analysis techniques, the system can effectively differentiate between legitimate and suspicious activities, helping to protect users from financial losses.
The heart of this project is the fraud detection model. Leveraging machine learning algorithms, the model learns from historical credit card transaction data to recognize patterns associated with fraud. By considering various features like transaction amount, location, and time, the model becomes adept at distinguishing normal transactions from fraudulent ones.
Dataset: https://www.kaggle.com/datasets/kartik2112/fraud-detection To train and test the model, I Have used dataset containing a collection of credit card transactions. Each transaction in the dataset is labeled as either legitimate or fraudulent. By feeding this data into the model, it learns to generalize and identify key indicators of fraudulent behavior.
- Data Cleaning
- Data Visualization
- Feature Extraction & Transformation
- Model Training
- Model Prediction