A data-centric annotation tool to increase the accuracy of your Named Entity Recognition projects which helps rapidly identify and fix labeling errors in your dataset. Import/export datasets in multiple formats, train a model and use it to aid in the annotation process. Setup an MLOps pipeline to experiment with different algorithms on the same data and increase their accuracy and performance in a data-centric way. Installation and Setup for Acharya are not required, Acharya runs the initial setup when run for the first time. Rapidly identify and fix labeling errors in your dataset. Import/export datasets in multiple formats, train a model and use it to aid in the annotation process. Setup an MLOps pipeline to experiment with different algorithms on the same data and increase their accuracy and performance in a data-centric way. Gain insights about your training & test data, distribution of annotated entities, and decide how to curate your data for better accuracy.

Features

  • Data-Centric dashboard
  • Advanced Workbench
  • In-built data versioning
  • Train, Test, Compare, Repeat
  • Auto labeling suggestions
  • Support for multiple data formats

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Categories

Data Labeling

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Registered

2023-05-23