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Open-Source Library for AI Model Explainability.

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Machine Learning Training Data

Overview

GAMMA FACET is an open-source library that provides insights into the inner workings of AI models.

Key Features:

  • Model inspection: FACET assesses how variables interact in ML models, uncovering relationships and revealing the true contributions of each variable.
  • Model simulation: FACET allows for testing what-if scenarios, pointing the way to better results and helping organizations focus their improvement efforts.
  • Transparency: By opening the black box of AI algorithms, FACET brings a new level of transparency, enabling business leaders to align their strategies with AI predictions.
  • Precision: FACET clarifies the roles of key parameters, allowing organizations to optimize their efforts with surgical precision.
  • Responsible AI: FACET fosters responsible AI by detecting and eliminating unfair bias, promoting objective decision making.

Use Cases:

  • Identifying variable interactions in machine learning models
  • Testing different scenarios to improve model performance
  • Promoting transparency and aligning business strategies with AI predictions

Benefits:

  • Gain transparency into AI algorithms
  • Focus improvement efforts
  • Foster responsible AI and objective decision making

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