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Friday, January 25 • 11:15am - 12:15pm
End-to-End Continuous Machine Learning in Production with PipelineAI, Spark ML, TensorFlow AI, PyTorch, Kafka, TPUs, and GPUs

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Traditional machine learning pipelines end with life-less models sitting on disk in the research lab.  These traditional models are typically trained on stale, offline, historical batch data. Static models and stale data are not sufficient to power today's modern, AI-first Enterprises that require continuous model training, continuous model optimizations, and lightning-fast model experiments directly in production. Through a series of open source, hands-on demos and exercises, we will use PipelineAI to breathe life into these models using 4 new techniques that we’ve pioneered:
* Continuous Validation (V)
* Continuous Optimizing (O)
* Continuous Training (T)
* Continuous Explainability (E).

The Continuous "VOTE" techniques has proven to maximize pipeline efficiency, minimize pipeline costs, and increase pipeline insight at every stage from continuous model training (offline) to live model serving (online.)
Attendees will learn to create continuous machine learning pipelines in production with PipelineAI, TensorFlow, and Kafka.

A laptop is required for this session. 

Speakers
avatar for Chris Fregly, PipelineAI

Chris Fregly, PipelineAI

Founder, PipelineAI
Chris Fregly is Founder at PipelineAI, a Real-Time Machine Learning and Artificial Intelligence Startup based in San Francisco. He is also an Apache Spark Contributor, a Netflix Open Source Committer, founder of the Global Advanced Spark and TensorFlow Meetup, author of the O’Reilly... Read More →


Friday January 25, 2019 11:15am - 12:15pm
Pacific G-H Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA