Streamlit for Machine Learning Cheat Sheet

The latest cheat sheet from KDnuggets demonstrates how to use Streamlit for building machine learning apps. Download the quick reference now.


Streamlit & Machine Learning Go Together

You undoubtedly already know what machine learning is. If not, you probably stumbled upon the wrong website. There is also a good chance you know about Streamlit, but I suppose there is a much better chance you are unfamiliar with it than with machine learning.

Streamlit is an open-source library that makes building data apps in Python easy. It takes care of the underlying web technologies so developers can focus on logic and interface. As such, Streamlit is a popular choice among data scientists and others who want to quickly create easily-sharable interactive data apps.

As mentioned above, putting the 2 together — machine learning and Streamlit — is a popular option for data scientists and other data professionals looking to experiment on data, prototype, or share results. Knowing how to quickly turn around data apps is becoming an essential skill for data folks, and this combination certainly allows for this. If you don't know how to use Streamlit, we suggest you learn now.

And this is where our latest cheat sheet comes in.


Streamlit for Machine Learning Cheat Sheet


Streamlit is an open-source library that makes building data apps in Python easy.


KDnuggets has put together a handy quick reference resource explaining and demonstrating the essential Streamlit syntax for building machine learning apps quickly. And Streamlit isn't relegated to machine learning only. Indeed, there's likely no faster way to create a dashboard for your interactive data science project regardless of its intent, from data cleaning, to data exploration, to interacting with databases.

Or even create something that has nothing to do with data science whatsoever. Think of it this way: if you can do it with Python, you can do it with Streamlit. And since your Streamlit project is written entirely in Python, if you already code in the language should be able to pick up the library usage without much trouble, especially with a handy quick reference resource, like this.

So download the cheat sheet, and check it out now, and don't forget to check back soon for more.