Banking and Credit Frauds

Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model from example inputs and using that to make predictions or decisions, rather than following strictly static program instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making.

Through this training we are going to guide you through the process of understanding the concept of credit frauds in bank using a case-study. We have used Kmeans and hierarchical clustering for understanding the data and also used other visualization techniques and methods to compare and understand the flow of Data.

Target Customers:
✓ Anyone who wants to learn about data and analytics
✓ Data Engineers
✓ Analysts
✓ Architects
✓ Software Engineers
✓ IT operations
✓ Technical managers

Pre-Requisites:
✓ Prior knowledge of machine learning required
✓ Usage of tools like R and SAS