Chainer vs Streamlit

Chainer vs Streamlit: What are the differences?

Developers describe Chainer as "A Powerful, Flexible, and Intuitive Framework for Neural Networks". It is an open source deep learning framework written purely in Python on top of Numpy and CuPy Python libraries aiming at flexibility. It supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort. On the other hand, Streamlit is detailed as "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.

Chainer and Streamlit can be categorized as "Machine Learning" tools.

Some of the features offered by Chainer are:

• Supports CUDA computation
• Runs on multiple GPUs
• Supports various network architectures

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

Chainer and Streamlit are both open source tools. Chainer with 5.1K GitHub stars and 1.34K forks on GitHub appears to be more popular than Streamlit with 2.73K GitHub stars and 184 GitHub forks.