Gluon vs Streamlit: What are the differences?
What is Gluon? Deep Learning API from AWS and Microsoft. 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.
What is Streamlit? A Python app framework built specifically for Machine Learning and Data Science teams. It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.
Gluon and Streamlit belong to "Machine Learning Tools" category of the tech stack.
Some of the features offered by Gluon are:
- 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.
On the other hand, Streamlit provides the following key features:
- Free and open source
- Build apps in a dozen lines of Python with a simple API
- No callbacks
Streamlit is an open source tool with 2.73K GitHub stars and 184 GitHub forks. Here's a link to Streamlit's open source repository on GitHub.