us250007

us250007's Stars

• shap/shap

  A game theoretic approach to explain the output of any machine learning model.

  Language:Jupyter Notebook22.8k2432.5k3.3k

• marcotcr/lime

  Lime: Explaining the predictions of any machine learning classifier

  Language:JavaScript11.6k2616341.8k

• karpathy/arxiv-sanity-preserver

  Web interface for browsing, search and filtering recent arxiv submissions

  Language:Python5.1k1681131.3k

• Teradata/covalent

  Teradata UI Platform built on Angular Material

  Language:TypeScript2.2k107978357

• johannfaouzi/pyts

  A Python package for time series classification

  Language:Python1.8k2582164

• jphall663/interpretable_machine_learning_with_python

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

  Language:Jupyter Notebook672426207

• fxs130430/SHAP_FOLD

  (Explainable AI) - Learning Non-Monotonic Logic Programs From Statistical Models Using High-Utility Itemset Mining

  Language:Prolog37509

• us8945/AWS_EMR_Pysparkling

  Set Up Python environment on AWS EMR cluster with H2O Sparkling Water (Pysparling)

  Language:Jupyter Notebook4100

• mtanco/teradata-kmeans

  Dynamically calculate cluster error for Teradata K-Means UDF

  Language:SQLPL1101