PRT: Pattern Recognition and Machine Learning in MATLAB
=========

A free and permissively licensed object oriented approach to machine learning in MATLAB.

Machine learning and pattern recognition are everywhere. MATLAB is a high level interpreted language widely used throughout academia and engineering due to its ease of use and numerous available toolboxes. Currently available toolboxes for pattern recognition and machine learning in MATLAB are either costly or restrictively licensed. The PRT is a MIT licensed toolbox that provides access to a wide range of pattern recognition techniques in an easy to use unified framework. The PRT provides a suite of MATLAB commands and data-types to help you organize, visualize, process, cluster and classify your data. If you have data and need to make predictions based on your data, the PRT can help.

* Blog and info: <http://newfolder.github.io/>
* Installation Guide: <http://newfolder.github.io/prtdoc/prtDocInstallation.html>
* Documentation: <http://newfolder.github.io/prtdoc>
* User Guide: http://newfolder.github.io/prtdoc/prtDocUsersGuide.html
PRT: Pattern Recognition and Machine Learning in MATLAB
=========

A free and permissively licensed object oriented approach to machine learning in MATLAB.

Machine learning and pattern recognition are everywhere. MATLAB is a high level interpreted language widely used throughout academia and engineering due to its ease of use and numerous available toolboxes. Currently available toolboxes for pattern recognition and machine learning in MATLAB are either costly or restrictively licensed. The PRT is a MIT licensed toolbox that provides access to a wide range of pattern recognition techniques in an easy to use unified framework. The PRT provides a suite of MATLAB commands and data-types to help you organize, visualize, process, cluster and classify your data. If you have data and need to make predictions based on your data, the PRT can help.

* Blog and info: <http://covartech.github.io/>
* Installation Guide: <http://covartech.github.io/prtdoc/prtDocInstallation.html>
* Documentation: <http://covartech.github.io/prtdoc>
* User Guide: http://covartech.github.io/prtdoc/prtDocUsersGuide.html
Update to README.md for new documentation directory
Update to README.md for new documentation directory
