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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 80 GitHub forks. Here’s a link to Propel's open source repository on GitHub

Who uses Propel?

Developers

Propel Integrations

Why developers like Propel?

Here’s a list of reasons why companies and developers use Propel
Top Reasons
Be the first to leave a pro
Propel Reviews

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

betocantu93
betocantu93
Ember.js
Ember.js
PHP
PHP
MySQL
MySQL
Propel
Propel
Slim
Slim
Intercom
Intercom

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
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.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
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.
ML Kit
ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.
See all alternatives

Propel's Followers
10 developers follow Propel to keep up with related blogs and decisions.
Tamilvanan P
Matt Erhart
Mark Niehe
ericp96
Nay Thein
René Milzarek
Kenneth Darling
krishna999
goodhope258
MohammadAsh15