Programming/Deep Learning

Deep Learning

Introduction

Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised or unsupervised.

There is a massive amount of possible applications where Deep Learning can be deployed, these include:

• Automatic speech recognition
• Image recognition
• Visual art processing
• Natural language processing
• Drug discovery and toxicology
• Customer relationship management
• Recommendation systems
• Bioinformatics
• Health diagnostics
• Image restoration
• Financial fraud detection

Development Environments

There are the following development environments already part of our HPC

• Python 3.5 with Tensorflow (and Keras), and theano.
• C/C++/Fortran with CUDA GPU programming.
• PGI compiler with openACC programming for C and Fortran.
• Matlab with deep learning libraries.

Further Information

• https://www.tensorflow.org/tutorials/

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