Machine Learning

Algorithms .. Credit Card Fraud

Introduction

A typical organization loses an estimated 5% of its yearly revenue to fraud.

In this lab we're going to:

• use TPOT (AutoML) to automatically discover well-performing models.

• apply supervised learning algorithms to detect fraudulent behavior based upon past fraud.

• use unsupervised learning methods to discover new types of fraud activities.

Fraudulent transactions are rare compared to the norm. As such, learn to properly classify imbalanced datasets.

To listen to the video please copy and paste the website URL into your host Chrome browser, as there's no soundcard in the Lab environment.

Lab Overview