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.

Data Analysis with the FraudFinder Workshop
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What you'll 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.
Skills you'll practice
Tools you'll use
Details to know

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About this project
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How you'll learn
Hands-on, project-based learning
Practice new skills by completing job-related tasks with step-by-step instructions.
No downloads or installation required
Access the tools and resources you need in a cloud environment.
Available only on desktop
This project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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