Amazon SageMaker EdgeAmazon
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Azure Machine LearningMicrosoft
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Related Products
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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.
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About
Accelerate the end-to-end machine learning lifecycle. Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible ML. Productivity for all skill levels, with code-first and drag-and-drop designer, and automated machine learning. Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Companies looking for an advance Machine Learning solution to easily operate machine learning models running on edge devices
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Audience
Data scientists, AI, and machine learning developers
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationAmazon
Founded: 2006
United States
aws.amazon.com/sagemaker/edge/
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Company InformationMicrosoft
Founded: 1975
United States
azure.microsoft.com/en-us/products/machine-learning/
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Categories |
Categories |
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Machine Learning Features
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Data Labeling Features
Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management
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Integrations
APERIO DataWise
Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Azure AI Search
Azure Data Science Virtual Machines
Azure Database for MariaDB
Azure Kinect DK
Azure Marketplace
Azure Percept
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Integrations
APERIO DataWise
Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Azure AI Search
Azure Data Science Virtual Machines
Azure Database for MariaDB
Azure Kinect DK
Azure Marketplace
Azure Percept
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