Name: Recommender Systems: Collaborative Filtering and Other Approaches
Start: 2018-05-17T18:00:00-06:00
End: 2018-05-17T20:00:00-06:00
Location: Galvanize- Platte Street

Recommender systems are everywhere. From Amazon to Netflix, recommender systems are the basis of the user-specific recommendations we see every day. We will cover the various types of recommender systems from Content-Based to Collaborative Filtering, examining their inner workings and use cases.

Make sure to register for this free event on Eventbrite: https://www.eventbrite.com/e/recommender-systems-collaborative-filtering-and-other-approaches-tickets-45354209662

About our Speaker - Chris Feller

Chris Feller is a Data Science Resident at Galvanize with a background in advanced analytics working for multiple NBA teams. Having recently completed the Data Science Immersive at Galvanize he will soon be joining Nike as a Data Scientist in Beaverton, Oregon.

About our Sponsor

Galvanize is the premiere dynamic learning community for technology. With campuses located in booming technology sectors throughout the country, Galvanize provides a community for each the following:

Education - part-time and full-time training in web development, data science, and data engineering

Workspace - whether you’re a freelancer, startup, or established business, we provide beautiful spaces with a community dedicated to support your company’s growth

Networking - events in the tech industry happen constantly in our campuses, ranging from popular Meetups to multi-day international conferences

To learn more about Galvanize, visit galvanize.com.

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Recommender Systems: Collaborative Filtering and Other Approaches

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Recommender Systems: Collaborative Filtering and Other Approaches

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