Abstract

Machine Learning models are easy to develop, but difficult to deploy, operationalize, and scale. One of the largest challenges, a challenge that affects all facets of Machine Learning work but particularly Mobile Apps, is data quality. This talk will cover the challenges we face when deploying models in parallel on Native Mobile applications and Cloud environments, the ways we improve data quality (and model quality) through active data governance, and the techniques we’re pioneering to improve models trained on small volumes of data.

Bio

Joe Reeve is an Engineering Manager and Staff Software Engineer at Amplitude, working primarily on Data Management. His experience ranges from Digital Strategy consulting, to Machine Learning on various platforms, to end-to-end Product development for start-ups, scale-ups, and charities. He has also successfully developed and maintained various mobile apps in these roles.