Streamlit Overview

Streamlit is an open-source Python library that can build user interfaces (UI) for various purposes, such as data science and machine learning applications and so on. Not only is it easy to learn, it’s also robust enough to create powerful and responsive web interfaces in a few lines of code.

Why should we use Streamlit?

Streamlit is a Python library that helps us develop UIs for our models without HTML, CSS, or JavaScript. Most machine learning models malfunction in Jupyter Notebook, and also aren’t very user-friendly with Streamlit, however, we can create a clean, responsive, and user-friendly UI for our models. Streamlit has the following salient features and advantages:

• We don’t need to deal with HTML, CSS, or JavaScript…

• It supports markdown.

• It has many prebuilt widgets available that can save us valuable time while we’re building the UI.

• It builds a responsive UI.

• Easy to deploy Streamlit apps using Streamlit sharing.

• It’s open-source, and we can create our own widgets if the need arises.

Build real-time web applications using Streamlit

In this course, we’ll learn how to build real-time web applications using Streamlit.

We’ll create the following projects from scratch:

• Build a UI for a model using Streamlit.

• Build a classification web app using Streamlit and sci-kit (sklearn).

• Build a Streamlit app to scrape Github profiles.

• Build a web app to transcribe audio using Python and AssemblyAI.

• Build a web app to display a word cloud of trending Google keywords and Twitter Hashtags using Streamlit.

• Build a web app to download YouTube videos in 30 lines of code.

Deploy the web application

At the end of the course, we’ll look at two different ways to deploy our web applications: Streamlit sharing and Heroku.