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Open-source library for scalable in-database analytics.

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MADlib Read Me
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MADlib is an open-source library for scalable in-database analytics. 
It provides data-parallel implementations of mathematical, statistical 
and machine learning methods for structured and unstructured data.

See the project web site located at http://madlib.net for links to the latest
binary and source packages.

For installation and contribution guides, please see the MADlib wiki at
https://github.com/madlib/madlib/wiki.

The latest documentation of MADlib modules can be found at http://doc.madlib.net
or can be accessed directly from the MADlib installation directory by opening
doc/user/html/index.html.

Changes between MADlib versions are described in the ReleaseNotes.txt file.

MADlib incorporates material from the following third-party components:
- argparse 1.2.1 "provides an easy, declarative interface for creating command
  line tools"
  http://code.google.com/p/argparse/
- Boost 1.46.1 (or newer) "provides peer-reviewed portable C++ source 
  libraries"
  http://www.boost.org/
- CERN ROOT is "an object oriented framework for large scale data analysis"
  http://root.cern.ch/
- doxypy 0.4.2 "is an input filter for Doxygen"
  http://code.foosel.org/doxypy
- Eigen 3.0.3 "is a C++ template library for linear algebra"
  http://eigen.tuxfamily.org/index.php?title=Main_Page
- PyYAML 3.10 "is a YAML parser and emitter for Python"
  http://pyyaml.org/wiki/PyYAML

License information regarding MADlib and included third-party libraries can be 
found inside the license directory.

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Open-source library for scalable in-database analytics.

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