Skip to content
Episode 2: How to use supervised Machine Learning to predict fraud episode artwork

May 13, 2020 48 min

Episode 2: How to use supervised Machine Learning to predict fraud

from Shared Experiences in GRC

You don’t have to be a data scientist to create powerful machine learning models! This week on Office Hours, Dan is joined by Kevin Leger, co-founder of Office Hours and Director of Product Design at Galvanize. They talk machine learning—from a real-world example of busting fraud to the confusion matrix (which is actually quite simple to understand). You'll also learn how to start using machine learning to find and predict instances of fraud in your organization.

Episode details come from the podcast's RSS feed.

Embed this episode

You don’t have to be a data scientist to create powerful machine learning models! This week on Office Hours, Dan is joined by Kevin Leger, co-founder of Office Hours and Director of Product Design at Galvanize. They talk machine learning—from a...

Ready to play

Episode 2: How to use supervised Machine Learning to predict fraud

0:00 48:28

No transcript yet.

Requests help us decide what to transcribe next.

Frequently asked questions

How long is this episode of Shared Experiences in GRC?

This episode is 48 minutes long.

When was this Shared Experiences in GRC episode published?

This episode was published on May 13, 2020.

Can I download this Shared Experiences in GRC episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.