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        "author": "Aaron Tuor",
        "author_email": "tuora@students.wwu.edu",
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            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Science/Research",
            "Operating System :: Unix",
            "Programming Language :: Python",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Scientific/Engineering :: Mathematics",
            "Topic :: Software Development :: Libraries",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "=========================================\nWelcome to Automated Neural Graph Toolkit\n=========================================\n\n|aaron| |docs| |pypi| \n\nPurpose\n-------\n\nAutomated Neural Graph Toolkit is an extension library for Google's Tensorflow. It is designed to facilitate rapid prototyping of Neural Network models which may consist of multiple models chained together. Multiple input streams and and or multiple output predictions are well supported.\n\nDocumentation for ANTk\n----------------------\n\nYou will find complete documentation for ANTk at `the ANTk readthedocs page`_.\n\n.. _the ANTk readthedocs page: http://antk.readthedocs.io/en/latest/\n\n\n.. |aaron| image:: docs/_static/snakelogo.png\n    :alt: Aaron's web page\n    :scale: 100%\n    :target: https://sw.cs.wwu.edu/~tuora/aarontuor/index.html\n\n.. |docs| image:: docs/_static/docs.gif\n    :alt: Documentation\n    :scale: 100%\n    :target: http://antk.readthedocs.io/en/latest\n    \n.. |pypi| image:: docs/_static/pypi_page.gif\n    :alt: pypi page\n    :scale: 100%\n    :target: https://pypi.python.org/pypi/antk/\n    \n.. _Install tensorflow: https://www.tensorflow.org/versions/r0.7/get_started/os_setup.html\n.. _Install graphviz: http://www.graphviz.org/\n\nPlatform\n--------\n\nANTk is compatible with linux 64 bit operating systems.\n\nPython Distribution\n-------------------\n\nANTk is written in python 2. Most functionality should be forwards compatible.\n\nInstall\n-------\n\nA virtual environment is recommended for installation. Make sure that tensorflow is installed in your virtual environment\nand graphviz is installed on your system.\n\n`Install tensorflow`_\n\n`Install graphviz`_\n\nFrom the terminal:\n\n.. code-block:: \n\n    (venv)$ pip install antk\n\n\n",
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        "keywords": "Deep Learning,Neural Networks,TensorFlow,Machine Learning,Western Washington University,Recommender Systems",
        "license": "none",
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        "name": "antk",
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        "summary": "Automated Neural-graph Toolkit: A Tensorflow wrapper for common deep learning tasks and rapid development of innovativemodels. Developed at Hutch Research, Western Washington University.Support for multiple input and output neural network graphs. Model visualizations and extensively documented interface. Explore tensorflow functionality and deep learning fundamentals.",
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