This is the initial extensions SDK release.

Machine learning (ML) interpret community package is used to interpret black box ML models.

• The TabularExplainer can be used to give local and global feature importances
• The best explainer is automatically chosen for the user based on the model
• Local feature importances are for each evaluation row
• Global feature importances summarize the most importance features at the model-level
• The API supports both dense (numpy or pandas) and sparse (scipy) datasets
• For more advanced users, individual explainers can be used
• The KernelExplainer and MimicExplainer are for BlackBox models
• The MimicExplainer is faster but less accurate than the KernelExplainer
• The TreeExplainer is for tree-based models
• The DeepExplainer is for DNN tensorflow or pytorch models

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