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Make your Machine Learning Models Come Alive with Streamlit
Use this free Python library to quickly serve models and display data
You made a machine learning model. Yippee! 😀 You want folks to be able to use it without firing up a Jupyter notebook. Hmm. 🤔 What should you do?
You could use Flask to serve your model. Flask is great lightweight web framework, but it requires knowing about routes and other web things. 😕 Django is a full-service framework, but with a steeper learning curve than Flask. If you just want to serve a model as quickly as possible, what should you use?
Streamlit to the rescue! With Streamlit you can serve a machine learning model in minutes, without learning a Javascript framework. 🚀
Streamlit is a newish open source library that uses Python and integrates well with common data science libraries. It handles interactivity and visualizations very well.
To paraphrase co-founder Adrien Treuille, Streamlit apps are Python scripts that treat widgets as variables, can reuse data and computations, and can be developed in a live coding environment. Streamlit is great for rapid development!
Quick Start:
Getting started with Streamlit is as easy as: