Neuropod vs Streamlit

Streamlit vs Neuropod: What are the differences?

Developers describe Streamlit 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. On the other hand, Neuropod is detailed as "Uber ATG's open source deep learning inference engine". It is a library that provides a uniform interface to run deep learning models from multiple frameworks in C++ and Python. It makes it easy for researchers to build models in a framework of their choosing while also simplifying productionization of these models.

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

Some of the features offered by Streamlit are:

• Free and open source
• Build apps in a dozen lines of Python with a simple API
• No callbacks

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

• Run models from any supported framework using one API
• Build generic tools and pipelines
• Fully self-contained models

Streamlit is an open source tool with 8.64K GitHub stars and 764 GitHub forks. Here's a link to Streamlit's open source repository on GitHub.