fraud_detect

Using a machine learning model to detect fraud in credit card transactions

This project uses data obtained from kaggle.com. It will analayze credit card transactions with a machine learning model and then identify whether transactions are fraudulent.

The dataset is too large to upload to Github. For the code to function properly, the dataset must be downloaded from https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud and placed in the root directory of the project.

The final output of the project is the Jupyter notebook file named 'fraud_detectv2.ipynb'.

To run this file:

1. Ensure that you have downloaded the 'creditcard.csv' dataset and placed it in the same directory as the notebook file 'fraud_detectv2.ipynb'.
2. Start Jupyter Notebook in the terminal with the command jupyter notebook. A browser window should open automatically. If not, follow the instruction in the terminal.
3. Navigate to the directory where the files are stored and open 'fraud_detectv2.ipynb'.
4. In the Menu at the top of the screen, click Kernel -> Restart & Run All
5. That's it! Once the code finishes running, scroll down and you can use the Descriptive and Non-Descriptive analyses.

Note: If the UI doesn't load properly the first time, Restart & Run All again.