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.
MXNet is a tool in the Machine Learning Tools category of a tech stack.
MXNet is an open source tool with GitHub stars and GitHub forks. Here’s a link to MXNet's open source repository on GitHub
Who uses MXNet?
Companies
6 companies reportedly use MXNet in their tech stacks, including Avito, bentoml, and Red Hat BIDS.
Developers
42 developers on StackShare have stated that they use MXNet.
MXNet Integrations
JavaScript, Python, Java, Scala, and Clojure are some of the popular tools that integrate with MXNet. Here's a list of all 7 tools that integrate with MXNet.
Pros of MXNet
2
MXNet's Features
- Lightweight
- Portable
- Flexible distributed/Mobile deep learning
MXNet Alternatives & Comparisons
What are some alternatives to MXNet?
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/
Theano
Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray).
Gluon
A new open source deep learning interface which allows developers to more easily and quickly build machine learning models, without compromising performance. Gluon provides a clear, concise API for defining machine learning models using a collection of pre-built, optimized neural network components.
