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1
Introduction
2
Welcome
3
Agenda
4
Machine Learning Process
5
Machine Learning Project
6
Label Data
7
Build Model
8
Recap
9
Machine Learning Algorithms
10
Deployment
11
SageMaker Web Console
12
SageMaker Key Features
13
Machine Learning
14
Price
15
Model Plane
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Greengrass
17
Demo
18
SageMaker Ground Truth
19
SageMaker Notebook
20
Download SageMaker
21
Deploy Green Grass
22
Visualize and Analyze Video
23
QA
24
Supported frameworks
25
Realtime video processing
26
Yellow 3 deployment
27
Possible applications
28
Features Infrastructure
29
Implementation on Nano
30
SD Card Images
31
Multiple Models
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StageMaker
33
Storage
34
Models on AWS
35
Optimized Training in SageMaker
36
SageMaker Performance
37
Lambda on Green Grass
38
Deploy custombuilt models
Description:
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

Nvidia
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#Computer Science #Internet of Things #AWS Greengrass #Machine Learning #Artificial Intelligence #Computer Vision #Neural Networks #Engineering #Electrical Engineering #Microcontrollers #Jetson Nano #Programming #Cloud Computing #Edge Computing #Data Labeling #Model Training
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Introduction