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About

The SageMaker Edge Agent allows you to capture data and metadata based on triggers that you set so that you can retrain your existing models with real-world data or build new models. Additionally, this data can be used to conduct your own analysis, such as model drift analysis. We offer three options for deployment. GGv2 (~ size 100MB) is a fully integrated AWS IoT deployment mechanism. For those customers with a limited device capacity, we have a smaller built-in deployment mechanism within SageMaker Edge. For customers who have a preferred deployment mechanism, we support third party mechanisms that can be plugged into our user flow. Amazon SageMaker Edge Manager provides a dashboard so you can understand the performance of models running on each device across your fleet. The dashboard helps you visually understand overall fleet health and identify the problematic models through a dashboard in the console.

About

Amazon SageMaker Model Training reduces the time and cost to train and tune machine learning (ML) models at scale without the need to manage infrastructure. You can take advantage of the highest-performing ML compute infrastructure currently available, and SageMaker can automatically scale infrastructure up or down, from one to thousands of GPUs. Since you pay only for what you use, you can manage your training costs more effectively. To train deep learning models faster, SageMaker distributed training libraries can automatically split large models and training datasets across AWS GPU instances, or you can use third-party libraries, such as DeepSpeed, Horovod, or Megatron. Efficiently manage system resources with a wide choice of GPUs and CPUs including P4d.24xl instances, which are the fastest training instances currently available in the cloud. Specify the location of data, indicate the type of SageMaker instances, and get started with a single click.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Companies looking for an advance Machine Learning solution to easily operate machine learning models running on edge devices

Audience

Companies in need of a solution to train ML models quickly and cost effectively

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Amazon
Founded: 2006
United States
aws.amazon.com/sagemaker/edge/

Company Information

Amazon
Founded: 1994
United States
aws.amazon.com/sagemaker/train/

Alternatives

Alternatives

Amazon SageMaker Ground Truth

Amazon SageMaker Ground Truth

Amazon Web Services

Categories

Categories

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Amazon SageMaker Unified Studio
BERT
CodeGPT
DALL·E 2
Hugging Face
NVIDIA NeMo Megatron
PyTorch
TensorFlow

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Amazon SageMaker Unified Studio
BERT
CodeGPT
DALL·E 2
Hugging Face
NVIDIA NeMo Megatron
PyTorch
TensorFlow
Claim Amazon SageMaker Edge and update features and information
Claim Amazon SageMaker Edge and update features and information
Claim Amazon SageMaker Model Training and update features and information
Claim Amazon SageMaker Model Training and update features and information