In this chapter, we used machine learning to detect financial fraud by handling imbalanced datasets. We also covered random under-sampling and oversampling. We looked at SMOTE as well as the modified version of SMOTE. Then we learned about detecting credit card fraud, which includes the logistic regression classifier and tuning hyperparameters.
This chapter also explained deep learning time as well as the Adam gradient optimizer. In the next chapter, we will explore a few different cybersecurity case studies.
