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Operationalizing Data Science Using Cloud Foundry
Recorded at:

| by Lawrence Spracklen Follow 0 Followers on Jan 12, 2017 | NOTICE: QCon.ai - Applied AI for Developers Apr 15 - 17, 2019, San Francisco. Save an extra $80 with INFOQAI19!
27:13

Summary
Lawrence Spracklen shows how a joint solution between Alpine’s Chorus Platform and Cloud Foundry closes the gap between data science insights and business value. He shows an example of creating a machine learning model leveraging data within MPP databases such as Apache HAWQ or Greenplum integrated with Chorus and then deploying this as a microservice within Cloud Foundry as a scoring engine.

Bio

Lawrence Spracklen leads engineering at Alpine. He is tasked with the continued development of Alpine’s advanced analytics platform. He brings to Alpine a diverse range of experiences, spanning processor design and research, distributed systems experience, software optimization and multi-thread scalability, security, and hardware accelerator development.

SpringOne Platform brings together the people, process and tools for delivering and operating software services. Learn and share with the startups and enterprises leveraging modern Java with Spring connecting all the pieces of the modern software puzzle from developer, operator, architect, data scientist to executive.

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