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Average Ratings 0 Ratings
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
Current models are costly to train, complicated to implement, challenging to validate, and notoriously susceptible to generating misleading information. At Symbolica, we are reimagining the process of machine learning from its foundation. By leveraging the highly expressive framework of category theory, we create models that can learn and understand algebraic structures. This approach equips our models with a comprehensive and systematic representation of the world that is both explainable and verifiable. Our goal is to empower developers and end users to grasp and articulate the reasons behind model outputs. This level of interpretability and control over the outputs—such as the ability to remove proprietary data from the training set—is essential for applications that are critical to mission success. Additionally, we believe that enhancing transparency in how models derive their conclusions will foster greater trust and collaboration between humans and machines.
API Access
Has API
API Access
Has API
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/clarify/
Vendor Details
Company Name
Symbolica
Website
www.symbolica.ai
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Product Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)