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 595,856 repositories, of these jphall663/interpretable_machine_learning_with_python is ranked #73,050 (88th percentile) for total stargazers, and #50,768 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #1,542/17,543.

jphall663/interpretable_machine_learning_with_python is also tagged with popular topics, for these it's ranked: python (#3,872/22324), machine-learning (#1,720/8063), data-science (#510/2138), data-mining (#66/292), interpretability (#29/169)

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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: 2024-12-15 @ 10:37am, id: 125130145 / R_kgDOB3VVoQ