Explore deploying AI with AWS ML IoT services on Jetson Nano in this comprehensive video tutorial. Learn about the machine learning process, including data labeling, model building, and deployment using SageMaker and AWS Greengrass. Discover key features of SageMaker, such as Ground Truth and Notebooks, and understand how to visualize and analyze video data. Gain insights into real-time video processing, possible applications, and infrastructure implementation on Jetson Nano. Delve into topics like optimized training, Lambda functions on Greengrass, and deploying custom-built models. Access additional resources and project files on GitHub to enhance your learning experience.
Deploy AI with AWS ML and IoT Services on Jetson Nano
Overview
Syllabus
Introduction
Welcome
Agenda
Machine Learning Process
Machine Learning Project
Label Data
Build Model
Recap
Machine Learning Algorithms
Deployment
SageMaker Web Console
SageMaker Key Features
Machine Learning
Price
Model Plane
Greengrass
Demo
SageMaker Ground Truth
SageMaker Notebook
Download SageMaker
Deploy Green Grass
Visualize and Analyze Video
QA
Supported frameworks
Realtime video processing
Yellow 3 deployment
Possible applications
Features Infrastructure
Implementation on Nano
SD Card Images
Multiple Models
StageMaker
Storage
Models on AWS
Optimized Training in SageMaker
SageMaker Performance
Lambda on Green Grass
Deploy custombuilt models
Taught by
NVIDIA Developer
