Hello Makers!

Join us this evening to discuss how engineers can deploy machine learning models!

Following is a brief agenda for the evening:

6 - 6:30 PM - Doors open & pizza
6:30 - 7:15 PM - Justin's Talk
7:15 - 7:45 PM - Q&A & Networking
7:45 - 8 PM - Contest for special prize!

Deploying machine learning models can be a pain point for many engineering teams. There are multiple avenues for success for a particular project but there can also be roads to disaster.

In this talk, I will discuss how to deploy Driverless AI pipelines. Topics will include the advantages & disadvantages for each deployment option - for example, why you might want to communicate to your scoring service over HTTP instead of using the language-level API. In addition, I will discuss general best practices that I have seen work & leave time to discuss your production questions - or new theories you now have as a result of the talk.

About Justin Loyola

Justin has been a Software Engineer at H2O.ai since 2016 working on Steam, H2O, & Driverless AI. Previously he worked at Captora, a marketing automation software company, & Google. He has focused on web development & has experience working on infrastructure operations, development operations, API development, & UI work. He earned his Bachelor's degree in History from UCSD & his Juris Doctorate from the University of Denver.