What is 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.
Gluon is a tool in the Machine Learning Tools category of a tech stack.
Gluon is an open source tool with 2.3K GitHub stars and 227 GitHub forks. Here’s a link to Gluon's open source repository on GitHub
Who uses Gluon?
23 developers on StackShare have stated that they use Gluon.
Pros of Gluon
Good learning materials
- Simple, Easy-to-Understand Code: Gluon offers a full set of plug-and-play neural network building blocks, including predefined layers, optimizers, and initializers.
- Flexible, Imperative Structure: Gluon does not require the neural network model to be rigidly defined, but rather brings the training algorithm and model closer together to provide flexibility in the development process.
- Dynamic Graphs: Gluon enables developers to define neural network models that are dynamic, meaning they can be built on the fly, with any structure, and using any of Python’s native control flow.
- High Performance: Gluon provides all of the above benefits without impacting the training speed that the underlying engine provides.
Gluon Alternatives & Comparisons
What are some alternatives to Gluon?
See all alternatives
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.
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
The fastest way to build beautiful Electron apps using simple HTML and CSS. Underneath it all is Electron. Originally built for GitHub's Atom text editor, Electron is the easiest way to build cross-platform desktop applications.
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.
It is a set of graphics and media packages that enables developers to design, create, test, debug, and deploy rich client applications that operate consistently across diverse platforms.