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Accelerating Apache Spark for Intelligent Edge Applications with Yaron Haviv (iguazio)

890 views · Published 11 October 2018 · 34:07 · Indexed 14 November 2026

Channel: Databricks · 2018 · Science & Technology

AI is shifting from batch processes to real-time, event-driven applications, requiring companies to process data at the edge of the network near the data sources. Edge data sources can be anything from a car, or wristwatch, to an industrial component gathering data from multiple machines in a factory.

Yaron Haviv will walk you through interactively developing AI applications with Spark ML and Spark streaming which run on hybrid environments, leveraging elasticity in the cloud and high performance at the edge. He will explain how to leverage Spark’s extensive set of AI tools and ability to process large data sets to create machine learning models in the public cloud, and seamlessly deploy them at the edge for immediate action.

Furthermore, participants will learn how to ensure models are constantly updated across cloud and edge and how to rapidly send sensor data from the edge to the cloud. The session will include live IIoT demos of real-world customer use-cases such as detection of patterns in historical data sets to learn about machinery, predict outcomes and make correlations with real-time fresh data.

About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business.
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Accelerating Apache Spark for Intelligent Edge Applications with Yaron Haviv (iguazio)

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