Completely real-time recommendations

Dear friends,

This time we will have Thomas Lojko, Senior Director of Systems Engineering at MapR to talk about real-time recommendation.

Abstract:

Currently deployed recommendation technology almost always provides real-time recommendations based on a model that is developed using off-line techniques. The use of off-line training severely limits the ability to deal with fast changing content such as news or auctions. I will describe techniques which make it possible to move this training load into true real-time without loss of accuracy. Real-time training of recommendations is rarely done, partly because existing algorithms require periodic off-line training to correct accumulating inaccuracies. The techniques that I will describe do not require off-line training of any kind. In addition, the techniques described in this talk are easy to implement using stream processing, noSQL databases and search engines.

About Speaker:

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Thomas is a Senior Director of Systems Engineering at MapR. Thomas has over 15 years of experience as a technologist, including strong experience building, managing and inspiring teams to handle technical sales, implementation and support. Prior to joining MapR, Thomas was a Data Solutions Lead in Financial Services for Ayasdi, an advanced analytics company that provides machine learning software to Fortune 500 companies. Prior to Ayasdi, Thomas was the BRS SE Manager, Global Accounts for EMC, where he managed a team of pre-sales engineers to support global accounts. Prior to that role, he was the Senior Manager and Data Protection Advisor at EMC, where he managed a team with responsibilities for pre-sales, post-sales and product support across two product sets. Earlier in his career, Thomas was Vice President of Technical Services for WysDM, where he built the technical services team and served as the main technical contact for OEM and reseller partners. Thomas also held Systems Engineer, Project Manager, and Channel Technical Manager roles at Micromuse.

Thomas has a B.S. in Computer Science from Columbia University, and an MBA from the NYU Stern School of Business.

Agenda:

6 :30 pm: Guests arrival & networking.

7: 00 pm: Completely real-time recommendations

8.00pm: Event ends.

Our Sponsor: O'Reilly

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