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report](https://avatars.githubusercontent.com/in/12526?s=20\u0026v=4 \"You can find the coverage report here\")](https://sonarcloud.io/dashboard?id=vmware-daml-annotation-app)\n\n\u003cdiv align='center'\u003e \u003ch1\u003eData Annotator for Machine Learning\u003c/h1\u003e \u003c/div\u003e\n\nData Annotator for Machine Learning (DAML) is an application that helps machine learning teams facilitating the creation and management of annotations.\n\nCore features include:\n\n- Support for common annotation tasks:\n  - Text classification\n  - Named entity recognition\n  - Tabular classification and regresion\n  - Images recognition with bounding boxes and polygons\n  - Log labeling\n  - Question answer\n- Active learning with uncertainly sampling to query unlabeled data\n- Project tracking with real time data aggregation and review process\n- User management panel with role-based access control\n- Data management\n  - Import in common data formats\n  - Export in ML friendly formats\n  - Data sharing through community datasets\n- Swagger API for programmatic labeling, connecting to data pipelines and more\n\n\u003cbr\u003e\n\n## Helpful links\n\n- [ATO 2021 talk](https://www.youtube.com/watch?v=n0WghXqCH5o)\n- [DAML medium article](https://medium.com/vmware-data-ml-blog/introducing-data-annotator-for-machine-learning-e8af2f19497a)\n- [User guide](https://github.com/vmware/data-annotator-for-machine-learning/wiki/DAML-User-Guide)\n- [Tutorial](https://github.com/vmware/data-annotator-for-machine-learning/wiki/Tutorial:-Using-DAML-to-Label-the-Sentiment-of--VMware-Reddit-and-Twitter-Comments)\n- [DAML release note](https://github.com/vmware/data-annotator-for-machine-learning/releases)\n\n\n## What is included\n\nDAML project includes three components:\n\n- annotation-app: Angular application for the UI\n- annotation-service: Backend services built with Node \u0026 Express\n- active-learning-service: Django application providing active learning api using modAL library for pool-based uncertainty sampling to rank the unlabelled data\n\n## Quick start\n\n- For the docker version usage to see [run with docker documentation](RUN-WITH-DOCKER.md)\n- For development environment and build configuration see [build documentation](BUILD.md)\n- For the slack integration configuration see [manifest documentation](docs/manifest.yml)\n\n## Contributing\n\nDAML project team welcomes contributions from the community. For more detailed information, see [CONTRIBUTING.md](CONTRIBUTING.md).\n\n## Bugs and feature requests\n\nHave 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.\n\u003cbr\u003e\n\n## Copyright and license\n\nCopyright 2019-2021 VMware, Inc.\nSPDX-License-Identifier: Apache-2.0.\n","funding_links":[],"categories":["Text"],"sub_categories":["Open source"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvmware-archive%2Fdata-annotator-for-machine-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvmware-archive%2Fdata-annotator-for-machine-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvmware-archive%2Fdata-annotator-for-machine-learning/lists"}