Virtual Model Optimization Using the Deep Learning Workbench on Intel® DevCloud for the Edge
April 1, 2021
8:00 AM Pacific Daylight Time (GMT-7:00)
The event is at capacity. For information on future events in your area, please visit the Intel Software Developer Zone
The Deep Learning (DL) Workbench is a key model optimization feature of the Intel® Distribution of the OpenVINO™ toolkit. This feature can now be accessed virtually, with no installation or hardware configuration, using the Intel® DevCloud for the Edge, a remote development environment with access to the latest Intel® hardware and software. In this webinar, Intel experts will demonstrate the capabilities of the DL Workbench on DevCloud for the Edge and demonstrate how users can use an object detection sample to test the features or upload their own model and access a wide range of Intel hardware virtually.
Support Team
Rama Dorairaju
Rama is a System Engineer focused on solving problems related to Edge Computing by bringing easy access to accelerated AI. Rama has 20+ years of experience in Embedded systems, Satellite broadcast technologies, Mobile computing, and IoT/Edge Computing domains, with a strong understanding of computer vision, cloud architectures and ML/DL Workloads.
Jason Domer
Developer Experience Architect, Intel Corporation
Jason is a System Engineer focused on Edge Cloud Technology Integration and Telemetry, helping drive accelerated AI prototyping on Intel hardware and empowering internal/external customers to make data driven decisions. Jason has 20+ years of experience in software development, contributing to the Java Media Framework, developing the ACH payment system for an Intel/VISA start-up, integrating Intel’s x86 emulation technology into McAfee’s Anti-Virus Engine, and prototyping security software/hardware for the Internet-of-Things.
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