Datature Features
What are the features of Datature?
Deployment
- Framework Flexibility
- Ease of Deployment
- Scalability
- Framework Flexibility
- Versioning
- Ease of Deployment
- Scalability
Management
- Model Registry
Quality
- Task Quality
Image Annotation
- Image Segmentation
- Object Detection
- Data Types
Operations
- Metrics
- Infrastructure management
- Collaboration
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Filter for Features
Deployment
Language Flexibility | Allows users to input models built in a variety of languages. 17 reviewers of Datature have provided feedback on this feature. | 80% (Based on 17 reviews) | |
Framework Flexibility | Allows users to choose the framework or workbench of their preference. This feature was mentioned in 19 Datature reviews. | 88% (Based on 19 reviews) | |
Versioning | Records versioning as models are iterated upon. This feature was mentioned in 18 Datature reviews. | 93% (Based on 18 reviews) | |
Ease of Deployment | As reported in 20 Datature reviews. Provides a way to quickly and efficiently deploy machine learning models. | 96% (Based on 20 reviews) | |
Scalability | As reported in 20 Datature reviews. Offers a way to scale the use of machine learning models across an enterprise. | 95% (Based on 20 reviews) | |
Framework Flexibility | Allows users to choose the framework or workbench of their preference. This feature was mentioned in 20 Datature reviews. | 88% (Based on 20 reviews) | |
Versioning | As reported in 19 Datature reviews. Records versioning as models are iterated upon. | 95% (Based on 19 reviews) | |
Ease of Deployment | Provides a way to quickly and efficiently deploy machine learning models. 19 reviewers of Datature have provided feedback on this feature. | 95% (Based on 19 reviews) | |
Scalability | Based on 21 Datature reviews. Offers a way to scale the use of machine learning models across an enterprise. | 93% (Based on 21 reviews) |
Management
Cataloging | Records and organizes all machine learning models that have been deployed across the business. 17 reviewers of Datature have provided feedback on this feature. | 86% (Based on 17 reviews) | |
Monitoring | Tracks the performance and accuracy of machine learning models. This feature was mentioned in 18 Datature reviews. | 91% (Based on 18 reviews) | |
Governing | Provisions users based on authorization to both deploy and iterate upon machine learning models. This feature was mentioned in 16 Datature reviews. | 88% (Based on 16 reviews) | |
Model Registry | Allows users to manage model artifacts and tracks which models are deployed in production. This feature was mentioned in 19 Datature reviews. | 92% (Based on 19 reviews) | |
Cataloging | Records and organizes all machine learning models that have been deployed across the business. 16 reviewers of Datature have provided feedback on this feature. | 88% (Based on 16 reviews) | |
Monitoring | Based on 17 Datature reviews. Tracks the performance and accuracy of machine learning models. | 92% (Based on 17 reviews) | |
Governing | As reported in 16 Datature reviews. Provisions users based on authorization to both deploy and iterate upon machine learning models. | 85% (Based on 16 reviews) |
Quality
Labeler Quality | Based on 17 Datature reviews. Gives user a metric to determine the quality of data labelers, based on consistency scores, domain knowledge, dynamic ground truth, and more. | 94% (Based on 17 reviews) | |
Task Quality | As reported in 19 Datature reviews. Ensures that labeling tasks are accurate through consensus, review, anomaly detection, and more. | 91% (Based on 19 reviews) | |
Data Quality | Ensures the data is of a high quality as compared to benchmark. This feature was mentioned in 18 Datature reviews. | 88% (Based on 18 reviews) | |
Human-in-the-Loop | As reported in 18 Datature reviews. Gives user the ability to review and edit labels. | 94% (Based on 18 reviews) |
Automation
Machine Learning Pre-Labeling | Uses models to predict the correct label for a given input (image, video, audio, text, etc.). 18 reviewers of Datature have provided feedback on this feature. | 94% (Based on 18 reviews) | |
Automatic Routing of Labeling | Automatically route input to the optimal labeler or labeling service based on predicted speed and cost. 14 reviewers of Datature have provided feedback on this feature. | 95% (Based on 14 reviews) |
Image Annotation
Image Segmentation | Based on 19 Datature reviews. Has the ability to place imaginary boxes or polygons around objects or pixels in an image. | 94% (Based on 19 reviews) | |
Object Detection | has the ability to detect objects within images. 19 reviewers of Datature have provided feedback on this feature. | 98% (Based on 19 reviews) | |
Object Tracking | As reported in 16 Datature reviews. Track unique object IDs across multiple video frames | 78% (Based on 16 reviews) | |
Data Types | Supports a range of different types of images (satelite, thermal cameras, etc.) This feature was mentioned in 18 Datature reviews. | 88% (Based on 18 reviews) |
Natural Language Annotation
Named Entity Recognition | As reported in 17 Datature reviews. Gives user the ability to extract entities from text (such as locations and names). | 52% (Based on 17 reviews) | |
Sentiment Detection | Gives user the ability to tag text based on its sentiment. This feature was mentioned in 13 Datature reviews. | 31% (Based on 13 reviews) | |
OCR | Gives user the ability to label and verify text data in an image. This feature was mentioned in 15 Datature reviews. | 50% (Based on 15 reviews) |
Operations
Metrics | As reported in 21 Datature reviews. Control model usage and performance in production | 93% (Based on 21 reviews) | |
Infrastructure management | Deploy mission-critical ML applications where and when you need them 18 reviewers of Datature have provided feedback on this feature. | 87% (Based on 18 reviews) | |
Collaboration | Based on 19 Datature reviews. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. | 91% (Based on 19 reviews) |
