In this kernel, we are going to predict whether a credit card is fraud or not using Machine Learning.
The datasets contains transactions made by credit cards in September 2013 by european cardholders. This dataset presents transactions that occurred in two days, where we have 492 frauds out of 284,807 transactions. The dataset is highly unbalanced, the positive class (frauds) account for 0.172% of all transactions.
Due to confidentiality issues, the input variables are transformed into numerical using PCA transformations.
The dataset is taken from kaggle here.
Note: I am not including the dataset file in this repository because of its size. You can download it from the aforementioned kaggle link.