{ "info": { "author": "Frootlab Developers", "author_email": "contact@frootlab.org", "bugtrack_url": null, "classifiers": [ "Development Status :: 2 - Pre-Alpha", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Operating System :: OS Independent", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.7", "Topic :: Database :: Database Engines/Servers", "Topic :: Scientific/Engineering :: Artificial Intelligence", "Topic :: Scientific/Engineering :: Information Analysis", "Topic :: Software Development :: Libraries :: Python Modules" ], "description": "
\n
\n \"Machine\n
\n
\n\nVivid Node\n==========\n\n[![Building Status](https://travis-ci.org/frootlab/rian.svg?branch=master)](https://travis-ci.org/frootlab/rian)\n[![Documentation Status](https://readthedocs.org/projects/rian/badge/?version=latest)](https://rian.readthedocs.io/en/latest/?badge=latest)\n[![PIP Version](https://badge.fury.io/py/rian.svg)](https://badge.fury.io/py/rian)\n\n*Vivid Node* (alias *Rian*) is a free [Python](https://www.python.org/) library\nfor next generation machine learning- and data analysis applications, that\nimplement *cloud-assisted meta programming*. Rian is part of the\n[Vivid Code](http://www.frootlab.org/vivid) framework and actively developed at\nthe [Frootlab](http://www.frootlab.org) Organization.\n\nThe key goal of Rian is to automate and support collaborative data science. To\nachieve this goal Rian orchestrates established frameworks like\n[TensorFlow\u00c2\u00ae](https://www.tensorflow.org) or [Keras\u00c2\u00ae](https://keras.io) and\ndynamically extends their capabilities by cloud based community algorithms.\nThereby Rian allows the usage of abstract defined algorithms, that are specified\nwith respect to their category, the used data type and an evaluation metric.\nDuring runtime these abstract specifications are resolved cloud-sided by\n*currently best fitting* algorithm, that match the specification. This allows\nthe separation of engineering and data science, as well as simple collaborations\nbetween organizations without the requirement to share data.\n\n
\n
\n \"Collaborative\n
\n
\n Collaborative data science using the Vivid Code framework\n
\n
\n
\n\nFor a given algorithm category and data type, the currently best fitting\nalgorithms are determined by the used metric. Examples for such metrices would\nbe the prediction accuracies within a fixed set of gold standard samples of the\nrespective domain of application (e.g. latin handwriting, spoken words, TCGA\ngene expression data, etc.).\n\nCurrent Development Status\n--------------------------\n\nRian currently is in *Pre-Alpha* development stage, which immediately follows\nthe *Planning* stage. This means, that at least some essential requirements of\nRian are not yet implemented.\n\nInstallation\n------------\n\nComprehensive information and installation support is provided within the\n[online manual](http://docs.frootlab.org/rian). If you already have a\nPython environment configured on your computer, you can install the latest\ndistributed version by using pip:\n\n $ pip install rian\n\nOr alternatively:\n\n $ pip install vivid-node\n\nDocumentation\n-------------\n\nThe documentation of the latest distributed version is available as an [online\nmanual](http://docs.frootlab.org/rian) and for download, given in the\nformats [PDF](https://readthedocs.org/projects/rian/downloads/pdf/latest/),\n[EPUB](https://readthedocs.org/projects/rian/downloads/epub/latest/) and\n[HTML](https://readthedocs.org/projects/rian/downloads/htmlzip/latest/).\n\nContribution\n------------\n\nContributors are very welcome! Feel free to report bugs, ideas and feature\nrequests to the [issue tracker](https://github.com/frootlab/rian/issues),\nprovided by GitHub. Currently, as our team still is growing, we do not provide\nany Contribution Guide Lines. So, if you are interested to help or to join the\nteam, we would be glad, to [hear about you](mailto:application@frootlab.org).\n\nLicense\n-------\n\nRian is open source software and available free for any use under the\n[GPLv3 license](https://www.gnu.org/licenses/gpl.html):\n\n \u00c2\u00a9 2019 The Frootlab Organization\n \u00c2\u00a9 2013-2019 Patrick Michl\n\n\n", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://www.frootlab.org/rian", "keywords": "data-analysis enterprise-data-analysis data-science collaborative-data-science data-visualization machine-learning artificial-intelligence deep-learning probabilistic-graphical-model", "license": "GPLv3", "maintainer": "", "maintainer_email": "", "name": "vivid-node", "package_url": "https://pypi.org/project/vivid-node/", "platform": "", "project_url": "https://pypi.org/project/vivid-node/", "project_urls": { "Homepage": "https://www.frootlab.org/rian" }, "release_url": "https://pypi.org/project/vivid-node/0.5.583/", "requires_dist": [ "rian (>=0.5.583)" ], "requires_python": ">=3.7", "summary": "Enterprise Machine-Learning and Predictive Analytics", "version": "0.5.583" }, "last_serial": 5873112, "releases": { "0.5.583": [ { "comment_text": "", "digests": { "md5": "b11e5aa68d0500039fc3f401225cf931", "sha256": "a2dbbef3c3b32bd1ab540ec31389fbf52eb69ee54ec87cdafcec1f554c216e2d" }, "downloads": -1, "filename": "vivid_node-0.5.583-py3-none-any.whl", "has_sig": false, "md5_digest": "b11e5aa68d0500039fc3f401225cf931", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": ">=3.7", "size": 16696, "upload_time": "2019-09-23T09:24:56", "url": "https://files.pythonhosted.org/packages/0d/67/5c23bd0fa9db4c9ffca31cca14b6377f975353f8096bd6a63c91e1d58cef/vivid_node-0.5.583-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "e2fa5d2a65e663fb22e217d4ed852f14", "sha256": "84dadebfe9497aa05e06defd7fc244661162d0ca0dbb6207440ef37144d208dd" }, "downloads": -1, "filename": "vivid_node-0.5.583.tar.gz", "has_sig": false, "md5_digest": "e2fa5d2a65e663fb22e217d4ed852f14", "packagetype": "sdist", "python_version": "source", "requires_python": ">=3.7", "size": 4401, "upload_time": "2019-09-23T09:24:58", "url": "https://files.pythonhosted.org/packages/1e/05/ced472dc3fd15a24e233c22f7f16bb3543e14c21279bb0501cf33a19cdba/vivid_node-0.5.583.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "b11e5aa68d0500039fc3f401225cf931", "sha256": "a2dbbef3c3b32bd1ab540ec31389fbf52eb69ee54ec87cdafcec1f554c216e2d" }, "downloads": -1, "filename": "vivid_node-0.5.583-py3-none-any.whl", "has_sig": false, "md5_digest": "b11e5aa68d0500039fc3f401225cf931", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": ">=3.7", "size": 16696, "upload_time": "2019-09-23T09:24:56", "url": "https://files.pythonhosted.org/packages/0d/67/5c23bd0fa9db4c9ffca31cca14b6377f975353f8096bd6a63c91e1d58cef/vivid_node-0.5.583-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "e2fa5d2a65e663fb22e217d4ed852f14", "sha256": "84dadebfe9497aa05e06defd7fc244661162d0ca0dbb6207440ef37144d208dd" }, "downloads": -1, "filename": "vivid_node-0.5.583.tar.gz", "has_sig": false, "md5_digest": "e2fa5d2a65e663fb22e217d4ed852f14", "packagetype": "sdist", "python_version": "source", "requires_python": ">=3.7", "size": 4401, "upload_time": "2019-09-23T09:24:58", "url": "https://files.pythonhosted.org/packages/1e/05/ced472dc3fd15a24e233c22f7f16bb3543e14c21279bb0501cf33a19cdba/vivid_node-0.5.583.tar.gz" } ] }