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Welcome to the Azimuth Documentation!

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Azimuth is an open source application that helps AI practitioners and data scientists better understand their dataset and model predictions by performing thorough dataset and error analyses. The application leverages different tools, including robustness tests, semantic similarity analysis and saliency maps, unified by concepts such as smart tags and proposed actions.

While this version of Azimuth focuses on NLP classification problems, the tool could easily be adapted to apply to other data types and models, e.g. vision or tabular use cases. However, the current focus is on text classification.

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Documentation Structure

  • Getting Started contains all the instructions to install and launch the app. It also details the changelog of our releases.
  • Key Concepts explains the different concepts and analyses that are provided in Azimuth to perform dataset and error analysis.
  • User Guide goes screen per screen to explain the different interactions and visualizations available.
  • Reference details the config file and the custom objects which allow configuring Azimuth with different datasets and pipelines.
  • Development guides on how to develop and contribute to the repo.

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