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 74 GitHub forks. Here’s a link to Propel's open source repository on GitHub
Who uses Propel?
Propel Integrations
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.
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.
