Get Advice Icon

Need advice about which tool to choose?Ask the StackShare community!

Propel
Propel

2
10
+ 1
0
PyTorch
PyTorch

275
260
+ 1
11
Add tool

Propel vs PyTorch: What are the differences?

What is Propel? Machine learning for JavaScript. Propel provides a GPU-backed numpy-like infrastructure for scientific computing in JavaScript.

What is PyTorch? A deep learning framework that puts Python first. 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.

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

Propel and PyTorch are both open source tools. PyTorch with 29.6K GitHub stars and 7.18K forks on GitHub appears to be more popular than Propel with 2.81K GitHub stars and 81 GitHub forks.

What is Propel?

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

What is 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.
Get Advice Icon

Need advice about which tool to choose?Ask the StackShare community!

Why do developers choose Propel?
Why do developers choose PyTorch?
    Be the first to leave a pro
      Be the first to leave a con
        Be the first to leave a con
        What companies use Propel?
        What companies use PyTorch?
          No companies found

          Sign up to get full access to all the companiesMake informed product decisions

          What tools integrate with Propel?
          What tools integrate with PyTorch?

          Sign up to get full access to all the tool integrationsMake informed product decisions

          What are some alternatives to Propel and PyTorch?
          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/
          ML Kit
          ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.
          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
          Decisions about Propel and PyTorch
          Conor Myhrvold
          Conor Myhrvold
          Tech Brand Mgr, Office of CTO at Uber · | 6 upvotes · 508.4K views
          atUber TechnologiesUber Technologies
          TensorFlow
          TensorFlow
          Keras
          Keras
          PyTorch
          PyTorch

          Why we built an open source, distributed training framework for TensorFlow , Keras , and PyTorch:

          At Uber, we apply deep learning across our business; from self-driving research to trip forecasting and fraud prevention, deep learning enables our engineers and data scientists to create better experiences for our users.

          TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users. It also combines high performance with an ability to tinker with low-level model details—for instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA’s CUDA toolkit.

          Uber has introduced Michelangelo (https://eng.uber.com/michelangelo/), an internal ML-as-a-service platform that democratizes machine learning and makes it easy to build and deploy these systems at scale. In this article, we pull back the curtain on Horovod, an open source component of Michelangelo’s deep learning toolkit which makes it easier to start—and speed up—distributed deep learning projects with TensorFlow:

          https://eng.uber.com/horovod/

          (Direct GitHub repo: https://github.com/uber/horovod)

          See more
          Interest over time
          Reviews of Propel and PyTorch
          No reviews found
          How developers use Propel and PyTorch
          Avatar of Yonas B.
          Yonas B. uses PyTorchPyTorch

          I used PyTorch when i was working on an AI application, image classification using deep learning.

          How much does Propel cost?
          How much does PyTorch cost?
          Pricing unavailable
          Pricing unavailable
          News about Propel
          More news
          News about PyTorch
          More news