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Pinned

  1. A curated list of awesome machine learning interpretability resources.

    2.7k 497

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

    Jupyter Notebook 616 194

  3. Materials for GWU DNSC 6279 and DNSC 6290.

    Jupyter Notebook 227 173

  4. Practical ideas on securing machine learning models

    TeX 32 6

  5. kdd_2019 Public

    Paper and talk from KDD 2019 XAI Workshop

    TeX 20 5

  6. GWU_rml Public

    Jupyter Notebook 25 22

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October 2022

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