mlstatpy: détours mathématiques autour du machine learning
==========================================================
.. image:: https://ci.appveyor.com/api/projects/status/5env33qptorgshaq?svg=true
:target: https://ci.appveyor.com/project/sdpython/mlstatpy
:alt: Build Status Windows
.. image:: https://circleci.com/gh/sdpython/mlstatpy/tree/main.svg?style=svg
:target: https://circleci.com/gh/sdpython/mlstatpy/tree/main
.. image:: https://badge.fury.io/py/mlstatpy.svg
:target: https://pypi.org/project/mlstatpy/
.. image:: https://img.shields.io/badge/license-MIT-blue.svg
:alt: MIT License
:target: https://opensource.org/license/MIT/
.. image:: https://codecov.io/github/sdpython/mlstatpy/coverage.svg
:target: https://codecov.io/github/sdpython/mlstatpy/
.. image:: http://img.shields.io/github/issues/sdpython/mlstatpy.png
:alt: GitHub Issues
:target: https://github.com/sdpython/mlstatpy/issues
Le module contient essentiellement des digressions mathématiques
autour du machine learning. Parmi les choses intéressantes,
une courbe *ROC* avec intervalle de confiance, détection
automatique de segment dans une image, un algorithme
d'autocomplétion, une distance d'édition entre graphes,
des petites choses pour les données de Wikipedia,
un algorithme de conversion d'un arbre de décision en
réseaux de neurones.
The package mostly contains documentation. It also implements
some code rarely needed such as ROC curve with bandwidth,
automated segment detection in a image, some simple autocomplete
algorithm, a graph edit distance, some helpers on Wikipedia data,
an algorithm to convert decision trees into neural network.
* `documentation <https://sdpython.github.io/doc/mlstatpy/dev/>`_
Raw data
{
"_id": null,
"home_page": "https://github.com/sdpython/mlstatpy",
"name": "mlstatpy",
"maintainer": null,
"docs_url": null,
"requires_python": null,
"maintainer_email": null,
"keywords": null,
"author": "Xavier Dupr\u00e9",
"author_email": "xavier.dupre@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/fc/4d/10c2878afc282713dde30fd6863151410cb19c2c5c489c78a6853ef2cb4e/mlstatpy-0.4.0.tar.gz",
"platform": null,
"description": "mlstatpy: d\u00e9tours math\u00e9matiques autour du machine learning\n==========================================================\n\n.. image:: https://ci.appveyor.com/api/projects/status/5env33qptorgshaq?svg=true\n :target: https://ci.appveyor.com/project/sdpython/mlstatpy\n :alt: Build Status Windows\n\n.. image:: https://circleci.com/gh/sdpython/mlstatpy/tree/main.svg?style=svg\n :target: https://circleci.com/gh/sdpython/mlstatpy/tree/main\n\n.. image:: https://badge.fury.io/py/mlstatpy.svg\n :target: https://pypi.org/project/mlstatpy/\n\n.. image:: https://img.shields.io/badge/license-MIT-blue.svg\n :alt: MIT License\n :target: https://opensource.org/license/MIT/\n\n.. image:: https://codecov.io/github/sdpython/mlstatpy/coverage.svg\n :target: https://codecov.io/github/sdpython/mlstatpy/\n\n.. image:: http://img.shields.io/github/issues/sdpython/mlstatpy.png\n :alt: GitHub Issues\n :target: https://github.com/sdpython/mlstatpy/issues\n\nLe module contient essentiellement des digressions math\u00e9matiques\nautour du machine learning. Parmi les choses int\u00e9ressantes,\nune courbe *ROC* avec intervalle de confiance, d\u00e9tection\nautomatique de segment dans une image, un algorithme\nd'autocompl\u00e9tion, une distance d'\u00e9dition entre graphes,\ndes petites choses pour les donn\u00e9es de Wikipedia,\nun algorithme de conversion d'un arbre de d\u00e9cision en\nr\u00e9seaux de neurones.\n\nThe package mostly contains documentation. It also implements\nsome code rarely needed such as ROC curve with bandwidth,\nautomated segment detection in a image, some simple autocomplete\nalgorithm, a graph edit distance, some helpers on Wikipedia data,\nan algorithm to convert decision trees into neural network.\n\n* `documentation <https://sdpython.github.io/doc/mlstatpy/dev/>`_\n",
"bugtrack_url": null,
"license": null,
"summary": "Points de d\u00e9tails li\u00e9s au machine learning",
"version": "0.4.0",
"project_urls": {
"Homepage": "https://github.com/sdpython/mlstatpy"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "fbda34163d60544cb85e327454766a56611607adf6dbc379e083b4ab78b67c46",
"md5": "8e3ceaac7036ca7e6b2ef410738ca17b",
"sha256": "1c68fc51125eacf84c1798e68a45c8cb44cea69e7f4e54677c192d396ad7d67d"
},
"downloads": -1,
"filename": "mlstatpy-0.4.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "8e3ceaac7036ca7e6b2ef410738ca17b",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 79964,
"upload_time": "2024-10-07T21:59:06",
"upload_time_iso_8601": "2024-10-07T21:59:06.280511Z",
"url": "https://files.pythonhosted.org/packages/fb/da/34163d60544cb85e327454766a56611607adf6dbc379e083b4ab78b67c46/mlstatpy-0.4.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "fc4d10c2878afc282713dde30fd6863151410cb19c2c5c489c78a6853ef2cb4e",
"md5": "f4a3db160eda63b21c030f931a966f19",
"sha256": "74e5ebac8fddc7f9a7895de210d4b252c6cb092a9ef8f2c0faff422aff69de4b"
},
"downloads": -1,
"filename": "mlstatpy-0.4.0.tar.gz",
"has_sig": false,
"md5_digest": "f4a3db160eda63b21c030f931a966f19",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 71871,
"upload_time": "2024-10-07T21:59:07",
"upload_time_iso_8601": "2024-10-07T21:59:07.586106Z",
"url": "https://files.pythonhosted.org/packages/fc/4d/10c2878afc282713dde30fd6863151410cb19c2c5c489c78a6853ef2cb4e/mlstatpy-0.4.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-10-07 21:59:07",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "sdpython",
"github_project": "mlstatpy",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [],
"lcname": "mlstatpy"
}
JSON
