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Description

The SageMaker Edge Agent enables the collection of data and metadata triggered by your specifications, facilitating the retraining of current models with real-world inputs or the development of new ones. This gathered information can also serve to perform various analyses, including assessments of model drift. There are three deployment options available to cater to different needs. GGv2, which is approximately 100MB in size, serves as a fully integrated AWS IoT deployment solution. For users with limited device capabilities, a more compact built-in deployment option is offered within SageMaker Edge. Additionally, for clients who prefer to utilize their own deployment methods, we accommodate third-party solutions that can easily integrate into our user workflow. Furthermore, Amazon SageMaker Edge Manager includes a dashboard that provides insights into the performance of models deployed on each device within your fleet. This dashboard not only aids in understanding the overall health of the fleet but also assists in pinpointing models that may be underperforming, ensuring that you can take targeted actions to optimize performance. By leveraging these tools, users can enhance their machine learning operations effectively.

Description

Protégé benefits from a robust network of users from academia, government, and industry, who utilize it to create knowledge-driven solutions across various fields such as biomedicine, e-commerce, and organizational modeling. Its versatile plug-in architecture allows for the development of both straightforward and intricate ontology-based applications. Developers have the capability to connect Protégé's outputs with rule systems or other problem-solving tools, enabling the creation of a diverse array of intelligent systems. Crucially, the dedicated Stanford team, alongside the extensive Protégé community, is readily available to provide assistance. This community actively engages by answering inquiries, contributing to documentation, and developing plug-ins. Furthermore, Protégé's foundation in Java enhances its extensibility, while its plug-and-play environment ensures it serves as a flexible platform for quick prototyping and application development, paving the way for innovative projects and solutions.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)

Integrations

Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

2006

Country

United States

Website

aws.amazon.com/sagemaker/edge/

Vendor Details

Company Name

Center for Biomedical Informatics Research

Country

United States

Website

protege.stanford.edu/

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Alternatives

Alternatives

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Amazon SageMaker Ground Truth

Amazon Web Services
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