A beginner’s guide to Streamlit

Ever wondered how to deploy your machine learning model in the form of an app, without using ML Studio, Flask or Django? Well, there’s a pretty effective solution that goes by the name Streamlit.

What is Streamlit, you may ask?

It’s an open-source framework that allows you to create machine learning and data science apps for free. So if you’ve worked extensively on your deep learning project or some cool data visualizations, and want to showcase your intellect and efforts, here’s your chance.

Did I mention it’s absolutely free?

Why should I use Streamlit?

• it’s based on Python — the syntax is pretty simple
• a respite from front-end development
• saves a lot of time; I mean it. You can have a fully functional and responsive app in less than 100 LOC!
• pre-designed widgets like buttons, checkboxes, and sliders accessible by just one command
• automatically detect changes in the Python source code whenever it’s saved, and runs it
• aesthetic design
• growing community forum

Sample application developed using Streamlit (via Streamlit Gallery)

Installing Streamlit