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Fraud Detection Case Study

The final case study in the Data Science Immersive at Galvanize in Seattle.

Background

Premise

You are a contract data scientist/consultant hired by a new e-commerce site to try to weed out fraudsters. The company unfortunately does not have much data science expertise... so you must properly scope and present your solution to the manager before you embark on your analysis. Also, you will need to build a sustainable software project that you can hand off to the companies engineers by deploying your model in the cloud. Since others will potentially use/extend your code you NEED to properly encapsulate your code and leave plenty of comments.

The Data

The data, provided by Galvanize, is a json file with other 14,000 events and 44 features. The data is considered sensitive and cannot be shared outside of Galvanize, so it will not be included out of this repository.

Files

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Built With

Team Members

Acknowledgments

  • The instructors at Galvanize: Matt Drury, Miles Erickson, and Jack Benneto

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Predicting fraud on an event management site

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