Amazon SageMaker Model Monitor 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.

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Company Details

Company:
Amazon
Year Founded:
2006
Headquarters:
United States
Website:
aws.amazon.com/sagemaker/model-monitor/

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Amazon SageMaker Model Monitor Screenshot 1
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Product Details

Platforms
Web-Based
Types of Training
Training Docs
Customer Support
Online Support

Amazon SageMaker Model Monitor Features and Options

Machine Learning Software

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

Amazon SageMaker Model Monitor Lists

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