WhyLabs Features

Deployment (10)

Language Flexibility: Allows users to input models built in a variety of languages. 17 reviewers of WhyLabs have provided feedback on this feature.
Framework Flexibility: As reported in 19 WhyLabs reviews. Allows users to choose the framework or workbench of their preference.
Versioning: As reported in 17 WhyLabs reviews. Records versioning as models are iterated upon.
Ease of Deployment: As reported in 19 WhyLabs reviews. Provides a way to quickly and efficiently deploy machine learning models.
Scalability: Offers a way to scale the use of machine learning models across an enterprise. 18 reviewers of WhyLabs have provided feedback on this feature.
Language Flexibility: Based on 18 WhyLabs reviews. Allows users to input models built in a variety of languages.
Framework Flexibility: Based on 20 WhyLabs reviews. Allows users to choose the framework or workbench of their preference.
Versioning: Records versioning as models are iterated upon. 17 reviewers of WhyLabs have provided feedback on this feature.
Ease of Deployment: Provides a way to quickly and efficiently deploy machine learning models. This feature was mentioned in 20 WhyLabs reviews.
Scalability: Based on 21 WhyLabs reviews. Offers a way to scale the use of machine learning models across an enterprise.

Cataloging: Based on 16 WhyLabs reviews. Records and organizes all machine learning models that have been deployed across the business.
Monitoring: Based on 21 WhyLabs reviews. Tracks the performance and accuracy of machine learning models.
Governing: Provisions users based on authorization to both deploy and iterate upon machine learning models. 15 reviewers of WhyLabs have provided feedback on this feature.
Model Registry: Allows users to manage model artifacts and tracks which models are deployed in production. 15 reviewers of WhyLabs have provided feedback on this feature.
Cataloging: Based on 15 WhyLabs reviews. Records and organizes all machine learning models that have been deployed across the business.
Monitoring: Tracks the performance and accuracy of machine learning models. This feature was mentioned in 20 WhyLabs reviews.
Governing: As reported in 16 WhyLabs reviews. Provisions users based on authorization to both deploy and iterate upon machine learning models.

Metrics: Control model usage and performance in production This feature was mentioned in 19 WhyLabs reviews.
Infrastructure management: Deploy mission-critical ML applications where and when you need them 16 reviewers of WhyLabs have provided feedback on this feature.
Collaboration: As reported in 18 WhyLabs reviews. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance.