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Description
Amazon SageMaker Clarify offers machine learning (ML) practitioners specialized tools designed to enhance their understanding of ML training datasets and models. It identifies and quantifies potential biases through various metrics, enabling developers to tackle these biases and clarify model outputs. Bias detection can occur at different stages, including during data preparation, post-model training, and in the deployed model itself. For example, users can assess age-related bias in both their datasets and the resulting models, receiving comprehensive reports that detail various bias types. In addition, SageMaker Clarify provides feature importance scores that elucidate the factors influencing model predictions and can generate explainability reports either in bulk or in real-time via online explainability. These reports are valuable for supporting presentations to customers or internal stakeholders, as well as for pinpointing possible concerns with the model's performance. Furthermore, the ability to continuously monitor and assess model behavior ensures that developers can maintain high standards of fairness and transparency in their machine learning applications.
Description
Craft personalized monitoring solutions for your machine learning models using our incredibly intuitive monitor builder, which alerts you to problems such as concept drift, declines in model performance, and bias, among other issues. Aporia effortlessly integrates with any machine learning infrastructure, whether you're utilizing a FastAPI server on Kubernetes, an open-source deployment solution like MLFlow, or a comprehensive machine learning platform such as AWS Sagemaker. Dive into specific data segments to meticulously observe your model's behavior. Detect unforeseen bias, suboptimal performance, drifting features, and issues related to data integrity. When challenges arise with your ML models in a production environment, having the right tools at your disposal is essential for swiftly identifying the root cause. Additionally, expand your capabilities beyond standard model monitoring with our investigation toolbox, which allows for an in-depth analysis of model performance, specific data segments, statistics, and distributions, ensuring you maintain optimal model functionality and integrity.
API Access
Has API
API Access
Has API
Integrations
Amazon SageMaker
Amazon S3
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Azure Blob Storage
Google Cloud Storage
Grafana Cloud
Jira
MLflow
Microsoft Teams
Integrations
Amazon SageMaker
Amazon S3
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Azure Blob Storage
Google Cloud Storage
Grafana Cloud
Jira
MLflow
Microsoft Teams
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/clarify/
Vendor Details
Company Name
Aporia
Website
www.aporia.com
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