Machine learning has quickly become the hot new tool in the big data ecosystem. Virtually every organization is looking to leverage machine learning and build deeper and richer predictive analytics into their applications.
How does this work though, in practice? What are the challenges organizations run into as they look to move hundreds of models into production? How can they
make the age of both data and models closer to real-time?
This session will focus on how leading practitioners have been able to scale their machine learning deployments in production with the MapR Converged Data Platform.
Use cases that will be featured include autonomous cars and analytics as a service for retail and financial services.
Sameer currently works with partners of MapR to bring joint solutions to market. Prior to that he led product marketing efforts for the MapR SQL-on Hadoop product set as well as Spark. He has over 15 years of experience in consulting, pre-sales and marketing across big data, analytics and business intelligence.