A Gaussian Naive Bayes ML classifier to classify credit card transactions as genuine or fraudulent. Credit card fraud detection dataset from kaggle (https://www.kaggle.com/mlg-ulb/creditcardfraud) was used in developing this project. Gaussian Naive Bayes is a classification machine learning algorithm which is an extension of Naive Bayes algorithm. Gaussian Naive Bayes is applied to data with real valued features.

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. To get a local copy up and running follow these simple example steps.

• python 3.6

sudo apt-get install python3.6

• jupyter notebook

sudo apt install jupyter

1. Clone the repository

git clone https://github.com/aashish157/Credit-Card-Fraud-Detection.git

1. Open the cloned Credit-Card-Fraud-Detection directory and save the credit card fraud dataset csv file with name creditcard.csv in a data folder
2. Open the .ipynb notebook file from cloned repo on Jupyter Notebook
3. Run all the cells to test the project

• [Jupyter Notebook] (https://jupyter.org/) - Python IDE
• [Python 3.6.8] (https://www.python.org/) - Programming language used

Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch
3. Commit your Changes
4. Push to the Branch
5. Open a Pull Request

• Aashish Raj Gupta - github - linkedin