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Data annotator for machine learning allows you to centrally create, manage and administer annotation projects for machine learning

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vmware/data-annotator-for-machine-learning

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Data Annotator for Machine Learning

Data Annotator for Machine Learning (DAML) is an application that helps machine learning teams facilitating the creation and management of annotations.

Core features include:

  • Support for common annotation tasks:
    • Text classification
    • Named entity recognition
    • Tabular classification and regresion
    • Images recognition with bounding boxes and polygons
    • Log labeling
    • Question answer
  • Active learning with uncertainly sampling to query unlabeled data
  • Project tracking with real time data aggregation and review process
  • User management panel with role-based access control
  • Data management
    • Import in common data formats
    • Export in ML friendly formats
    • Data sharing through community datasets
  • Swagger API for programmatic labeling, connecting to data pipelines and more

Helpful links

What is included

DAML project includes three components:

  • annotation-app: Angular application for the UI
  • annotation-service: Backend services built with Node & Express
  • active-learning-service: Django application providing active learning api using modAL library for pool-based uncertainty sampling to rank the unlabelled data

Quick start

Contributing

DAML project team welcomes contributions from the community. For more detailed information, see CONTRIBUTING.md.

Bugs and feature requests

Have a bug or a feature request? Please first read the issue guidelines and search for existing and closed issues. If your problem or idea is not addressed yet, please open a new issue.

Copyright and license

Copyright 2019-2021 VMware, Inc. SPDX-License-Identifier: Apache-2.0.