PyTorch is an open-source machine learning library for Python, based on Torch, used for applications such as natural language processing. One can also reuse Python packages such as NumPy, SciPy and Cython to extend PyTorch when needed.
PyTorch provides two high-level features:
- Tensor computation (like NumPy) with strong GPU acceleration
- Deep neural networks built on a tape-based autodiff system - README.md on GitHub repo
Automatic differentiation is done with a tape-based system at both a functional and neural network layer level. This functionality brings a high level of flexibility and speed as a deep learning framework and provides accelerated NumPy-like functionality.
PyTorch also includes standard defined neural network layers, deep learning optimizers, data loading utilities, and multi-gpu and multi-node support. Functions are executed immediately instead of enqueued in a static graph, improving ease of use and a sophisticated debugging experience. - NVIDIA - DEEP LEARNING FRAMEWORKS DOCUMENTATION
The Microsoft Cognitive Toolkit Massive Online Analysis (MOA) Apache MXNet (Incubating) Apache SystemML OpenCV Orange TensorFlow Apache Mahout Apache Spark Eclipse Deeplearning4j scikit-learn Torch Weka Yooreeka mlpack MALLET
The Microsoft Cognitive Toolkit Apache MXNet (Incubating) Apache SystemML TensorFlow Caffe Eclipse Deeplearning4j OpenNN Torch Weka
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