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#

machine-learning-interpretability

Here are 21 public repositories matching this topic...

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

  • UpdatedJun 17, 2024
  • Jupyter Notebook
explainx

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ ms8909@nyu.edu

  • UpdatedAug 21, 2024
  • Jupyter Notebook

An interpretable machine learning pipeline over knowledge graphs

  • UpdatedApr 30, 2025
  • Jupyter Notebook

TeleGam: Combining Visualization and Verbalization for Interpretable Machine Learning

  • UpdatedAug 11, 2019
  • JavaScript
INVASE

INVASE: Instance-wise Variable Selection . For more details, read the paper "INVASE: Instance-wise Variable Selection using Neural Networks," International Conference on Learning Representations (ICLR), 2019.

  • UpdatedAug 30, 2022
  • Python

Demonstration of InterpretME, an interpretable machine learning pipeline

  • UpdatedFeb 5, 2024
  • Jupyter Notebook

This project contains the data, code and results used in the paper title "On the relationship of novelty and value in digitalization patents: A machine learning approach".

  • UpdatedJul 13, 2022
  • Python

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