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MapR On Innovations in IoT, Machine Learning and Kubernetes at Convergence Dallas, Cloud Expo and Scale by the Bay

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MapR® Technologies, a provider of the industry’s leading data platform for AI and Analytics, announced its executives presented on various data topics, including IoT, machine learning and Kubernetes at industry events throughout November.

MapR conference session highlights included:

Convergence Dallas

When: Thursday, 08 November 2018 at 8:00 AM
Where: The Westin Galleria Dallas, TX
What: A full-day seminar, focused on busting through big data myths. MapR executives and technical experts will present on how to solve real-world problems by harnessing disruptions in data, artificial intelligence, cloud, containers, and edge technologies.

Jeff Schmitz, cloud solutions architect and Anna Drummond PhD, data science manager, at Sanchez Oil & Gas,  on “Using MapR in the Cloud to Accelerate Data Science.”

Read More: The AI Gold Rush: How to Make Money off AI and Machine Learning!

Cloud Expo

When: Monday, 12 November 2018 at 10:00 AM
Where: Roosevelt Hotel, New York, NY
What: William Peterson, vice president, industry solutions at MapR, will present on “IoT Data: From the Edge to the Cloud and Back.” This session explored a new way to think about next-gen applications and how to address the challenges of building applications that harness all data types and sources.

Read More: Calabrio Delivers Powerful Enterprise Scalability and Management Capabilities

Scale by the Bay

When: Saturday, 17 November 2018 at 9:50 AM
Where: Twitter HQ, San Francisco, CA
What: Skyler Thomas, engineer at MapR, will lead a talk on “Street Fighting Techniques for Multi-Tenant Machine Learning and Big Data Workloads on Kubernetes.” Skyler examined the various challenges in building an application that uses machine learning at scale in Kubernetes. He demonstrated how to launch many Spark clusters in a shared environment and the various tricks for making this work on Kubernetes at scale; using Kubeflow to train and serve deep learning models and GPU reservation and scheduling.

Read More: Interview with Ben Goertzel, CEO at SingularityNET

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