NVIDIA DeepStream embedded device deployment with Azure
|
In this module, you’ll publish and deploy an ARM-based DeepStream container workload to NVIDIA embedded hardware by using Azure IoT Edge.
Modify a DeepStream Graph Composer application to publish data to a hub in Azure IoT Hub., Build and publish cross-platform DeepStream container images to a container registry in Azure Container Registry., Configure Azure IoT Edge to run on NVIDIA embedded hardware., Deploy cross-platform DeepStream images to NVIDIA embedded devices by using Azure IoT Edge.
Prerequisites
x86-based system running Ubuntu 18.04
RTX 2080, RTX 3080, T4, or A100 NVIDIA graphics card
NVIDIA Jetson embedded device provisioned with JetPack 4.6
Familiarity with container workloads and Docker
Familiarity with Azure IoT Edge and Azure IoT Hub
Completion of the prerequisite module Introduction to NVIDIA DeepStream Graph Composer with Azure
User Reviews
Be the first to review “NVIDIA DeepStream embedded device deployment with Azure”
Related Products
Computer Vision
Study techniques and applications in computer vision for processing and interpreting visual data.
Building Generative Adversarial Networks
Learn to design and implement GANs for generating realistic data samples in various applications.
Generative AI
Discover the principles and applications of generative AI, including content creation and enhancement techniques.
Natural Language Processing
Explore natural language processing methods to enable machines to understand and generate human language.
AI for Healthcare
Understand the applications of AI in the healthcare sector, including diagnosis, treatment, and patient management.
Machine Learning Engineer with Microsoft Azure
Acquire the skills needed to build and deploy machine learning models using Microsoft Azure's tools and services.
There are no reviews yet.