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            "Development Status :: 5 - Production/Stable",
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            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Scientific/Engineering :: Information Analysis",
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        "description": "Discovery Foundation\n####################\n\nThe purpose of this foundation package is to provide a common platform through a set of abstractions that support the\ncore objectives of the Accelerated Machine Learning initiative. it applies the concepts of Parameterised Intent and\nits Separation of Concerns (SoC), based around advanced OOD patterns, to provide a common foundation to differing\nneeds of data scientist and productisation coders while sharing common ideas and their implementation.\n\n**Parametrized Intent** is a unique technique extracting the ideas and thinking of the data scientist or development\nspecialist from their discovery code and capturing it as intent with parameters that can be replayed in a\nproductionized environment. This decoupling and Separation of Concern between data, code and intended actions\nconsiderably improves transparancy of ideas, code reuse and reduced time to market.\n\n**Accelerated Machine Learning** is a unique approach around machine learning that innovates the data science discovery\nvertical and productization of the data science delivery model. More specifically, it is an incubator project that\nshadowed a team of Ph.D. data scientists in connection with the development and delivery of machine learning\ninitiatives to define measurable benefit propositions for customer success. To accomplish this, the project developed\nspecific and unique knowledge regarding transition and preparation of data sets for algorithmic execution and\naugmented knowledge, which is at the core of the projects services offerings. From this the project developed a new\napproach to data science discovery and productization dubbed \u201cAccelerated Machine Learning\u201d.\n\n.. class:: no-web no-pdf\n\n|pypi| |rdt| |license| |wheel|\n\n\n.. contents::\n\n.. section-numbering::\n\nInstallation\n============\n\npackage install\n---------------\n\n\n\nThe best way to install this package is directly from the Python Package Index repository using pip\n\n.. code-block:: bash\n\n    $ pip install discovery-foundation\n\nif you want to upgrade your current version then using pip\n\n.. code-block:: bash\n\n    $ pip install --upgrade discovery-foundation\n\nPackage Overview\n================\n\nClass Diagram\n-------------\n\nFrom the Class Diagram below the key abstarctions are the ``Abstracted Handlers`` and the\n``Abstracted Cleaners``\n\n.. image:: https://raw.githubusercontent.com/Gigas64/discovery-foundation/master/docs/images/ClassDiagram.png\n\nDataManager\n-----------\nthe ``DataManager`` class is a concrete implementation of the ``AbstractPropertiesManager`` and a built in\nextension of the foundation package to facilitate the management of contract properties of the connector handlers and\nparameterised intent\n\nAugmentedManager\n----------------\nthe ``AugmentedManager`` class is a concrete implementation of the ``AbstractPropertiesManager`` and a built in\nextension of the foundation package to facilitate the management of Augmented Knowledge.\n\n** Augmented Knowledge** is the capture of information on data, activities and the rich stream of subject matter\nexpertise, injected into the machine learning discovery vertical to provide an augmented n-view of the discovery\njourney. This might include security, sensitivity, data value scaling, data dictionary, terms of reference,\nobservations, performance, optimization, bias, etc. This enriched view of data allows, amongst other things,\nimproved knowledge share, AI explainability, feature transparency, and accountability that feeds into AI ethics,\nand insight analysis.\n\nReference\n=========\n\nPython version\n--------------\n\nPython 2.6 and 2.7 are not supported. Although Python 3.5 is supported, it is recommended to install\n``discovery-foundation`` against the latest Python 3.7.x whenever possible.\nPython 3 is the default for Homebrew installations starting with version 0.9.4.\n\nGitHub Project\n--------------\nDiscovery-Transitioning-Utils: `<https://github.com/Gigas64/discovery-foundation>`_.\n\nChange log\n----------\n\nSee `CHANGELOG <https://github.com/doatridge-cs/discovery-foundation/blob/master/CHANGELOG.rst>`_.\n\n\nLicence\n-------\n\nBSD-3-Clause: `LICENSE <https://github.com/doatridge-cs/discovery-foundation/blob/master/LICENSE.txt>`_.\n\n\nAuthors\n-------\n\n`Gigas64`_  (`@gigas64`_) created discovery-foundation.\n\n\n.. _pip: https://pip.pypa.io/en/stable/installing/\n.. _Github API: http://developer.github.com/v3/issues/comments/#create-a-comment\n.. _Gigas64: http://opengrass.io\n.. _@gigas64: https://twitter.com/gigas64\n\n\n.. |pypi| image:: https://img.shields.io/pypi/pyversions/Django.svg\n    :alt: PyPI - Python Version\n\n.. |rdt| image:: https://readthedocs.org/projects/discovery-foundation/badge/?version=latest\n    :target: http://discovery-transitioning-utils.readthedocs.io/en/latest/?badge=latest\n    :alt: Documentation Status\n\n.. |license| image:: https://img.shields.io/pypi/l/Django.svg\n    :target: https://github.com/Gigas64/discovery-foundation/blob/master/LICENSE.txt\n    :alt: PyPI - License\n\n.. |wheel| image:: https://img.shields.io/pypi/wheel/Django.svg\n    :alt: PyPI - Wheel\n\n\n\n",
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        "keywords": "Foundation SDK Machine learning AI connectivity data",
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