About this Webinar

Learn about new technologies including Azure Machine Learning and Device Lifecycle Management to enable you to deploy Azure and Azure IoT Edge to Industrial IoT Edge Gateways. Address existing remote monitoring and predictive maintenance applications with new tools and unlock your data to enable better insight and intelligence. Learn about the key fundamentals of Azure Machine learning, and the core concepts of Device Lifecycle Management. In addition, get the latest on how to deploy Azure IoT Edge and other technologies.  

What You’ll Learn by Attending this Webinar: 

  • Core principles of Device Lifecycle Management
  • Overview of Azure Machine Learning
  • How to deploy Azure IoT Edge today
  • How to apply Azure Machine Learning to an industrial application

Meet the presenters:


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Robert Jackson - Global IIoT Partner Program Manager

Robert has over 15 years of industrial and test and measurement experience. He started his career as a Product Manager where he helped launch first-generation Programmable Automation Controllers that re-defined the graphical software and COTs hardware approach for SCADA and control. Robert has also released new PCI-Express technologies for test and measurement applications and worked along-side partners to develop industry-leading case studies and application notes. Robert is currently the Global IIoT Partner Manager at Moxa where he is focused on developing an ecosystem of IIoT partners.

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Ted Way - Senior Program Manager, Microsoft Azure Machine Learning

Ted Way is a senior program manager on the AI and Advanced Architectures engineering team at Microsoft, focusing on hardware acceleration of AI algorithms in the cloud and edge. Previously he worked on the Azure Machine Learning platform, specifically on the accelerated AI service and integration of AI with Azure IoT Edge. He’s passionate about telling the story of how AI will empower people and organizations to achieve more. He holds BS degrees in electrical engineering and computer engineering, MS degrees in electrical engineering and biomedical engineering, and a PhD in biomedical engineering, all from the University of Michigan—Ann Arbor. His PhD dissertation was on “spell check for radiologists,” a computer-aided diagnosis (CAD) system that uses image processing and machine learning to predict lung cancer malignancy on chest CT scans.

 

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