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Description
Deep Learning Containers consist of Docker images that come preloaded and verified with the latest editions of well-known deep learning frameworks. They enable the rapid deployment of tailored machine learning environments, eliminating the need to create and refine these setups from the beginning. You can establish deep learning environments in just a few minutes by utilizing these ready-to-use and thoroughly tested Docker images. Furthermore, you can develop personalized machine learning workflows for tasks such as training, validation, and deployment through seamless integration with services like Amazon SageMaker, Amazon EKS, and Amazon ECS, enhancing efficiency in your projects. This capability streamlines the process, allowing data scientists and developers to focus more on their models rather than environment configuration.
Description
Amazon SageMaker Model Monitor enables users to choose which data to observe and assess without any coding requirements. It provides a selection of data types, including prediction outputs, while also capturing relevant metadata such as timestamps, model identifiers, and endpoints, allowing for comprehensive analysis of model predictions in relation to this metadata. Users can adjust the data capture sampling rate as a percentage of total traffic, particularly beneficial for high-volume real-time predictions, with all captured data securely stored in their designated Amazon S3 bucket. Additionally, the data can be encrypted, and users have the ability to set up fine-grained security measures, establish data retention guidelines, and implement access control protocols to ensure secure data handling. Amazon SageMaker Model Monitor also includes built-in analytical capabilities, utilizing statistical rules to identify shifts in data and variations in model performance. Moreover, users have the flexibility to create custom rules and define specific thresholds for each of those rules, enhancing the monitoring process further. This level of customization allows for a tailored monitoring experience that can adapt to varying project requirements and objectives.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon SageMaker
Yes
Amazon Web Services (AWS)
Yes
AWS Marketplace
Yes
AWS Neuron
Yes
Amazon EC2 G5 Instances
Yes
Amazon EC2 P4 Instances
Yes
Amazon EC2 P5 Instances
Yes
Amazon EC2 Trn1 Instances
Yes
Amazon EKS
Yes
Amazon Elastic Container Registry (ECR)
Yes
Integrations
Amazon SageMaker
Yes
Amazon Web Services (AWS)
Yes
AWS Marketplace
No
AWS Neuron
No
Amazon EC2 G5 Instances
No
Amazon EC2 P4 Instances
No
Amazon EC2 P5 Instances
No
Amazon EC2 Trn1 Instances
No
Amazon EKS
No
Amazon Elastic Container Registry (ECR)
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Amazon
Founded
2006
Country
United States
Website
aws.amazon.com/machine-learning/containers/
Vendor Details
Company Name
Amazon
Founded
2006
Country
United States
Website
aws.amazon.com/sagemaker/model-monitor/
Product Features
Container Management
Access Control
No
Application Development
No
Automatic Scaling
No
Build Automation
No
Container Health Management
No
Container Storage
No
Deployment Automation
No
File Isolation
No
Hybrid Deployments
No
Network Isolation
No
Orchestration
No
Shared File Systems
No
Version Control
No
Virtualization
No
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No