/credit-card-fraud-detection

Data analysis and neural network model development on credit card fraud data from Kaggle.

Primary LanguageJupyter Notebook

Data Analysis and Predictive Modeling on Credit Card Fraud Data

The Jupyter Notebook contains data analysis of credit card fraud data, and a predictive model to detect a fraudulent transaction. The predictive model is a neural network implemented in tensorflow.

The neural network implemented in tensorflow has three hidden layers and the hidden layer dimensions are: 29, 14, and 7.

Within the model I used the sigmoid cross entropy with logits as the cost function and we use Adam optimization to minimize the cost function.

The model ends up being trained on only a smaller portion of the data set due to computational complexity. I obtained a train and test accuracy of 100%.

I ran the Jupyter Notebook on a Kaggle kernel, which allowed me to utilize the entire data set. Here is a link: https://www.kaggle.com/stochasticats/neural-network-model-implemented-in-tensorflow/notebook