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Date: July 11, 2019
Time: 8:00am – 9:00am PT
Duration: 1 hour

Disaster response is a critical stage of disaster management and it requires quick decision-making. Deep learning–based inference systems can help you make intelligent predictions, —quickly—based on input data to provide insights in areas such as causal and location inferences.

This webinar is the first in a series of NVIDIA Federal webinars that will demonstrate how to train and deploy deep learning models. It will share real applications, such as disaster relief operations, which run anywhere from the tactical edge to the cloud.

Learn how to accelerate your AI inference applications by using NVIDIA’s TensorRT platform. Jonathan Howe, NVIDIA Solution Architect, will walk you through a TensorRT demo and answer your questions.

By attending this webinar, you'll learn to:
  • Train and deploy your deep learning model in the confines of its framework.
  • Optimize the layers of your deep learning model with TensorRT.
  • Develop a runtime into an application that operates on any NVIDIA GPU-accelerated platform.



You will receive an email with instructions on how to join the webinar shortly.

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Jonathan Howe

Senior Solution Architect, NVIDIA

Jonathan Howe joined the NVIDIA federal solution architecture team in 2017, specializing in deep learning and artificial intelligence for defense and intelligence applications. Howe has 12 years experience as a computer vision, data analysis, and physical modeling scientist and engineer at the UK's Ministry of Defence (MoD). He was selected as one of the UK government’s leading experts in deep learning and machine learning, winner of the MoD Chief Scientific Adviser award, recipient of the prestigious Arnold Award for outstanding applied research, and awarded an operational service medal for his field contributions while embedded within a US Processing Exploitation and Dissemination Cell in Afghanistan.

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Webinar: Description here

Date & Time: Wednesday, April 22, 2018