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These traditional statistics and computational applications are well suited for doing many aspects of ML. There are a number of textbooks and online documentation for using R, Matlab, and SAS to create ML analysis applications
To load R, Matlab, or SAS use
module load R/3.2.2module load matlab
or
module load SASR, Matlab, and SAS require a build-your-own skillset.
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Using Tensorflow
Tensorflow uses is built on python and there are two modules which load Tensorflow with either python2.7 or python3.5. Both modules should be used with the gpu partition (-p gpu) for best performance To load Tensorflow, type
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When using the python 3.5 version make sure to start python as python3. The Tensorflow site http://www.tensorflow.org has many examples and documentation for using this application.
Caffe
About
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Caffe ( from http://caffe.berkeleyvision.org/)
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and by community contributors.
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scikit-learn is installed as a library in python/2.7.6 and python/3.5.0. Load the 3.5.0 version of python that you need and run your python script. The scikit-learn library is called sklearn.
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