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

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RepositoryStats indexes 565,279 repositories, of these jphall663/interpretable_machine_learning_with_python is ranked #70,952 (87th percentile) for total stargazers, and #50,308 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #1,464/16,285.

jphall663/interpretable_machine_learning_with_python is also tagged with popular topics, for these it's ranked: python (#3,754/21414), machine-learning (#1,671/7698), data-science (#498/2054), data-mining (#64/281), interpretability (#29/154)

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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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updated: 2024-09-15 @ 11:37am, id: 125130145 / R_kgDOB3VVoQ