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What is Propel?

Propel provides a GPU-backed numpy-like infrastructure for scientific computing in JavaScript.
Propel is a tool in the Machine Learning Tools category of a tech stack.
Propel is an open source tool with 2.8K GitHub stars and 79 GitHub forks. Here鈥檚 a link to Propel's open source repository on GitHub

Who uses Propel?

Propel Integrations

Pros of Propel
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Public Decisions about Propel

Here are some stack decisions, common use cases and reviews by companies and developers who chose Propel in their tech stack.

Ember.js PHP MySQL Propel Slim Intercom

Mostly CRUD app, using propel orm, jsonapi serializers and ember.js frontend, this app was in ember 2.16 and we recently upgraded without any issue to 3.15, propel is super good as ORM, slim is a thin framework basically for routing and middleware

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Propel's Features

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

Propel Alternatives & Comparisons

What are some alternatives to Propel?
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.
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
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.
ML Kit
ML Kit brings Google鈥檚 machine learning expertise to mobile developers in a powerful and easy-to-use package.
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Propel's Followers
12 developers follow Propel to keep up with related blogs and decisions.
Di Mo Baay
Hershel Layton
Kenneth Darling
Tamilvanan P
Matt Erhart
Ren茅 Milzarek
Mark Niehe