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Keras

870
902
+ 1
12
MXNet

38
62
+ 1
1
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Keras vs MXNet: What are the differences?

What is Keras? Deep Learning library for Theano and TensorFlow. Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/.

What is MXNet? A flexible and efficient library for deep learning. A deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, it contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly.

Keras and MXNet belong to "Machine Learning Tools" category of the tech stack.

Some of the features offered by Keras are:

  • neural networks API
  • Allows for easy and fast prototyping
  • Convolutional networks support

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

  • Lightweight
  • Portable
  • Flexible distributed/Mobile deep learning

Keras and MXNet are both open source tools. It seems that Keras with 43.2K GitHub stars and 16.5K forks on GitHub has more adoption than MXNet with 17.5K GitHub stars and 6.21K GitHub forks.

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Pros of Keras
Pros of MXNet
  • 5
    Quality Documentation
  • 4
    Easy and fast NN prototyping
  • 3
    Supports Tensorflow and Theano backends
  • 1
    User friendly

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Cons of Keras
Cons of MXNet
  • 3
    Hard to debug
    Be the first to leave a con

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    What is Keras?

    Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

    What is MXNet?

    A deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, it contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly.

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    What companies use MXNet?
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    What tools integrate with Keras?
    What tools integrate with MXNet?

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    What are some alternatives to Keras and MXNet?
    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.
    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.
    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.
    TensorFlow.js
    Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API
    See all alternatives