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        "description": ".. image:: https://travis-ci.org/ottogroup/palladium.svg?branch=master\n    :target: https://travis-ci.org/ottogroup/palladium\n    :alt: Build status\n\n.. image:: https://coveralls.io/repos/ottogroup/palladium/badge.svg?branch=master\n    :target: https://coveralls.io/r/ottogroup/palladium\n    :alt: Test coverage status\n\n.. image:: https://readthedocs.org/projects/palladium/badge/?version=latest\n    :target: https://palladium.readthedocs.io/en/latest/\n    :alt: Documentation status\n\n.. image:: https://img.shields.io/pypi/v/palladium.svg\n    :target: https://pypi.python.org/pypi/palladium/\n    :alt: Latest version\n\n.. image:: https://img.shields.io/pypi/pyversions/palladium.svg\n    :target: https://pypi.python.org/pypi/palladium/\n    :alt: Supported Python versions\n\n.. image:: https://img.shields.io/pypi/l/palladium.svg\n    :target: https://pypi.python.org/pypi/palladium/\n    :alt: License\n\nPalladium\n=========\n\nPalladium provides means to easily set up predictive\nanalytics services as web services.  It is a **pluggable framework**\nfor developing real-world **machine learning solutions**.  It provides\ngeneric implementations for things commonly needed in machine\nlearning, such as dataset loading, model training with parameter\nsearch, a web service, and persistence capabilities, allowing you to\nconcentrate on the core task of developing an accurate machine\nlearning model.  Having a well-tested core framework that is used for\na number of different services can lead to a reduction of costs during\ndevelopment and maintenance due to harmonization of different services\nbeing based on the same code base and identical processes. Palladium\nhas a web service overhead of a few milliseconds only, making it\npossible to **set up services with low response times**.\n\nA **configuration file** lets you conveniently tie together existing\ncomponents with components that you developed.  As an example, if what\nyou want to do is to develop a model where you load a dataset from a\nCSV file or an SQL database, and train an SVM classifier to predict\none of the rows in the data given the others, and then find out about\nyour model's accuracy, then that's what Palladium allows you to do\n**without writing a single line of code**. However, it is also\npossible to independently integrate own solutions.\n\n.. image:: https://raw.githubusercontent.com/ottogroup/palladium/master/docs/palladium_illustration.png\n   :width: 700px\n   :align: center\n   :alt: Illustration of Palladium\n\n|\n\nMuch of Palladium's functionality is based on the **scikit-learn**\nlibrary.  Thus, a lot of times you will find yourself looking at the\n`documentation for scikit-learn <http://scikit-learn.org/>`_ when\ndeveloping with Palladium.  Although being implemented in Python,\nPalladium provides support for other languages and is shipped with\nexamples how to **integrate and expose R and Julia models**.\n\nFor an efficient deployment of services based on Palladium, a script to\n**create Docker images automatically** is provided. In order to manage\nand monitor a number of Palladium service instances in a cluster,\n**Mesosphere\u2019s Mesos framework Marathon can be used for deployment**,\nalso enabling **scalability by having a variable number of service\nnodes behind a load balancer**.  Examples how to create Palladium\nDocker images and how to use them with Mesos / Marathon are part of\nthe documentation. Other important aspects \u2013 especially relevant in\nenterprise contexts for setting up productive services \u2013 like\n**authentication, logging, or monitoring, can be easily integrated via\npluggable decorator lists** in the configuration file of a service,\nkeeping track of service calls and corresponding permissions.\n\nEveryone is welcome to contribute to Palladium. More information on\nhow to to contribute can be found in the FAQ section of the\n`Palladium documentation <http://palladium.readthedocs.org>`_.\n\nLinks\n-----\n\n- Source code repository at GitHub: https://github.com/ottogroup/palladium\n- Documentation including installation instructions and tutorial: http://palladium.readthedocs.org\n- Mailing list: https://groups.google.com/forum/#!forum/pld-list\n- Maintainer: `Andreas Lattner <https://github.com/alattner>`_\n\n\n",
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