Introducing Azimuth, an open-source tool to understand datasets and models in text classification.

Introducing Azimuth, an open-source tool to understand datasets and models in text classification.

Introducing AZIMUTH, an open-source software project from ServiceNow. Azimuth is an open-source software application that helps AI practitioners 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. Learn more at https://blogs.servicenow.com/2022/introducing-azimuth-open-source-project.html.

  • Available Analyses*
  • Syntax Analysis
  • Similarity Analysis
  • Behavioral Testing
  • Model Quality Assessment
  • Uncertainty Quantification
  • Saliency Maps
  • Featured Tools*
  • Exploration Space
  • Proposed Actions
  • Smart Tags
  • Outcomes
  • Featuring Smart Tags*
  • Smart Tags narrow down your data samples to identify where your dataset or model needs attention.

ICYMI Here is the link to the Getting Started overview video: https://youtu.be/BcVinHUojsw

If you would like to use Azimuth for your own projects, please be so kind as to use the following citation:

@software{Branchaud-Charron_Azimuth_an_open-source_2022,
author = {Branchaud-Charron, Frederic and Gauthier-Melancon, Gabrielle and Marinier, Joseph and Brin, Lindsay and Tyler, Chris and Le, Di and Grande, Karine and Babu, Nandhini},
doi = {10.5281/zenodo.6511558},
month = {5},
title = {{Azimuth, an open-source dataset and error analysis tool for text classification}},
url = {https://github.com/ServiceNow/azimuth},
version = {2.1},
year = {2022}
}