Streamlit vs Tensorflow Lite

Streamlit vs Tensorflow Lite: What are the differences?

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.

What is Tensorflow Lite? Deploy machine learning models on mobile and IoT devices. It is a set of tools to help developers run TensorFlow models on mobile, embedded, and IoT devices. It enables on-device machine learning inference with low latency and a small binary size.

Streamlit and Tensorflow Lite 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, Tensorflow Lite provides the following key features:

• Lightweight solution for mobile and embedded devices
• Enables low-latency inference of on-device machine learning models with a small binary size
• Fast performance

Streamlit is an open source tool with 7.48K GitHub stars and 659 GitHub forks. Here's a link to Streamlit's open source repository on GitHub.