Streamlit for interactive Machine Learning Apps #MachineLearning #DataScience #Python #MLtools @streamlit @myelbows

Example of a Streamlit slider widget.


Last month Streamlit launched their front end tool for machine learning teams. The project is open-source and easy to get up and running. Streamlit fills the need for tooling somewhere between JuPyter notebooks and consumer applications that can be written in Python. In a recent medium articleAdriene Treuille breaks down the goals for Streamlit into 3 main parts:

  1. Embrace Python scripting. Streamlit apps are really just scripts that run from top to bottom…
  2. Treat widgets as variables. There are no callbacks in Streamlit! Every interaction simply reruns the script…
  3. Reuse data and computation. …Streamlit introduces a cache primitive that behaves like a persistent, immutable-by-default, data store that lets Streamlit apps safely and effortlessly reuse information.

Getting Streamlit up and running to create the example above took about 10 minutes AND creating a slider widget in one line of code is impressive! If you would like to learn more about implementing Streamlit, take a look at these articles. If you would like to contribute to the project, check out the Streamlit community. Also, take a look at Streamlit’s documentation and main concepts.

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