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  • Writer's pictureUzair Mohammed

Deploying Your Project With Streamlit

Now that we've made creations with AI, we want to share them with the world! In this workshop, we introduced Streamlit, a modern python framework that lets you create simple web demos of data science and AI projects.


Students learned how to use Streamlit to build interactive web apps of projects in in image processing, prediction, natural language processing, and more. As we build AI projects, it's important to have the ability to make them easily available to anyone on the internet. Members also learned how to deploy their Streamlit app to the cloud, showcasing the work they did throughout the semester.


Our Halloween themed streamlit demo

Try it Out!


If you want to follow along with this workshop to create your own Streamlit app, see the step-by-step instructions. This will guide you through the process of setting up a github repository, running your code locally, and finally, publishing it to Streamlit Cloud to share your site with everyone.



To learn more about what you can do with Streamlit, read the documentation, or view the Cheat sheet for a quick reference of its functionality.


More Streamlit Creations

If you are curious or want to learn from examples, there's a gallery of diverse projects people have published on Streamlit at streamlit.io/gallery, along with their source code.


We also encourage you to join the conversation about what members made with Streamlit by joining the MSU AI Club Discord server.


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