Data Analysis with the FraudFinder Workshop

About this course

This is a self-paced lab that takes place in the Google Cloud console. FraudFinder is a series of JupyterLabs that show how to implement an end-to-end Data to AI architecture works on Google Cloud, through a toy use case of real-time fraud detection system.

What you will learn

• To read historical payment transactions data stored in a data warehouse and from a live stream of new transactions, perform exploratory data analysis
• Feature engineering & ingest features into a Feature Store. Train a model using Feature Store. Register your model in a model registry
• Deploy your model to an endpoint. Real-time inference on your model with Feature Store. Monitor your model.