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  2. Comparison of deep learning software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_deep...

    Linux, macOS, Windows: Python: Python: Only on Linux No Yes No Yes Yes Keras: François Chollet 2015 MIT license: Yes Linux, macOS, Windows: Python: Python, R: Only if using Theano as backend Can use Theano, Tensorflow or PlaidML as backends Yes No Yes Yes [20] Yes Yes No [21] Yes [22] Yes MATLAB + Deep Learning Toolbox (formally Neural Network ...

  3. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface. [14] A number of pieces of deep learning software are built on top of PyTorch, including Tesla Autopilot, [15] Uber's Pyro, [16] Hugging Face's Transformers, [17] PyTorch Lightning, [18] [19] and Catalyst. [20] [21]

  4. Chainer - Wikipedia

    en.wikipedia.org/wiki/Chainer

    Chainer is an open source deep learning framework written purely in Python on top of NumPy and CuPy Python libraries. The development is led by Japanese venture company Preferred Networks in partnership with IBM, Intel, Microsoft, and Nvidia. [4] [5] [6] [7]

  5. Torch (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Torch_(machine_learning)

    Torch is an open-source machine learning library, a scientific computing framework, and a scripting language based on Lua. [3] It provides LuaJIT interfaces to deep learning algorithms implemented in C. It was created by the Idiap Research Institute at EPFL. Torch development moved in 2017 to PyTorch, a port of the library to Python. [4] [5] [6]

  6. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    TensorFlow is available on 64-bit Linux, macOS, Windows, and mobile computing platforms including Android and iOS. [ citation needed ] Its flexible architecture allows for easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs ), and from desktops to clusters of servers to mobile and edge devices .

  7. DeepSpeed - Wikipedia

    en.wikipedia.org/wiki/DeepSpeed

    The library is designed to reduce computing power and memory use and to train large distributed models with better parallelism on existing computer hardware. [2] [3] DeepSpeed is optimized for low latency, high throughput training.

  8. Caffe (software) - Wikipedia

    en.wikipedia.org/wiki/Caffe_(software)

    Caffe (Convolutional Architecture for Fast Feature Embedding) is a deep learning framework, originally developed at University of California, Berkeley. It is open source, under a BSD license. [4] It is written in C++, with a Python interface. [5]

  9. Orange (software) - Wikipedia

    en.wikipedia.org/wiki/Orange_(software)

    Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.