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Propel

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ScalaNLP

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Propel vs ScalaNLP: What are the differences?

Propel: Machine learning for JavaScript. Propel provides a GPU-backed numpy-like infrastructure for scientific computing in JavaScript; ScalaNLP: A suite of machine learning and numerical computing libraries. ScalaNLP is a suite of machine learning and numerical computing libraries.

Propel and ScalaNLP can be primarily classified as "Machine Learning" tools.

Some of the features offered by Propel are:

  • Run anywhere, in the browser or natively from Node
  • Target multiple GPUs and make TCP connections
  • PhD optional

On the other hand, ScalaNLP provides the following key features:

  • ScalaNLP is the umbrella project for several libraries:
  • Breeze is a set of libraries for machine learning and numerical computing
  • Epic is a high-performance statistical parser and structured prediction library

Propel and ScalaNLP are both open source tools. ScalaNLP with 2.91K GitHub stars and 674 forks on GitHub appears to be more popular than Propel with 2.81K GitHub stars and 81 GitHub forks.

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What is Propel?

Propel provides a GPU-backed numpy-like infrastructure for scientific computing in JavaScript.

What is ScalaNLP?

ScalaNLP is a suite of machine learning and numerical computing libraries.

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    What tools integrate with Propel?
    What tools integrate with ScalaNLP?
    What are some alternatives to Propel and ScalaNLP?
    TensorFlow
    TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
    PyTorch
    PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
    Keras
    Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
    scikit-learn
    scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
    CUDA
    A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
    See all alternatives