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.

Date Created 2018-03-14 (6 years ago)
Commits 169 (last one about a year ago)
Stargazers 673 (0 this week)
Watchers 42 (0 this week)
Forks 207
License unknown
Ranking

RepositoryStats indexes 612,937 repositories, of these jphall663/interpretable_machine_learning_with_python is ranked #74,311 (88th percentile) for total stargazers, and #51,069 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #1,580/18,242.

jphall663/interpretable_machine_learning_with_python is also tagged with popular topics, for these it's ranked: python (#3,930/22851),  machine-learning (#1,739/8233),  data-science (#515/2181),  data-mining (#66/293),  interpretability (#30/172)

Other Information

jphall663/interpretable_machine_learning_with_python has 2 open pull requests on Github, 4 pull requests have been merged over the lifetime of the repository.

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2 commits on the default branch (master) since jan '22

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Languages

The primary language is Jupyter Notebook but there's also others...

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updated: 2025-02-03 @ 04:50pm, id: 125130145 / R_kgDOB3VVoQ