The dataset is obtained from this Kaggle page (https://www.kaggle.com/mlg-ulb/creditcardfraud)

The notebook does some basic data cleaning and then tries to classify whether transactions are fraud or not.

The key point in this is that the dataset is imbalanced because of which we have to use techniques like Oversampling or Undersampling.

We tried a few approaches to check for recall and precision and also took a random tupple to verify the classification.

Note that the final recall score for the Logistic Regression model on the test set was 91%