16476

DeepPy: Pythonic deep learning

Anders Boesen Lindbo Larsen
Department of Applied Mathematics and Computer Science, Technical University of Denmark
DTU Compute Technical Report-2016-6, 2016
@article{larsen2016deeppy,

   title={DeepPy: Pythonic deep learning},

   author={Larsen, Anders Boesen Lindbo},

   year={2016},

   publisher={Technical University of Denmark (DTU)}

}

This technical report introduces DeepPy – a deep learning framework built on top of NumPy with GPU acceleration. DeepPy bridges the gap between highperformance neural networks and the ease of development from Python/NumPy. Users with a background in scientific computing in Python will quickly be able to understand and change the DeepPy codebase as it is mainly implemented using high-level NumPy primitives. Moreover, DeepPy supports complex network architectures by letting the user compose mathematical expressions as directed graphs. The latest version is available under the MIT license.
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