Streamlit: The Fastest Way to build Data Apps

Steven Kolawole

Data Science Machine-Learning Natural Language Processing Python 3 Visualization

See in schedule: Fri, Jul 30, 15:45-16:15 CEST (30 min) Download/View Slides

When we think about building Python-based data science apps, we think of Flask. But there is a better option now. Streamlit.

Streamlit is an open-source web framework that lets you create apps for your machine learning projects with deceptively simple Python scripts, in hours. It supports hot-reloading, so your app updates live as you edit and save your file. No need to mess with HTTP requests, HTML, JavaScript, etc. In a short sentence, there is no need to write any front-end code. All you need is your favorite editor and a browser.

In this talk, we’ll go through how to build a very simple Streamlit app step-by-step. I will also review the pros and cons of Streamlit, as regards other popular Python web frameworks being used by Data Scientists and ML Engineers.

Type: Talk (30 mins); Python level: Beginner; Domain level: Intermediate

Steven Kolawole

Steven is a CS finalist, with a skillset in between Software Engineering and Data Science...So most times, he is a Machine Learning Engineer.
He's been interested in a wide range of applications of Data Science/ML from building scalable ML applications to helping businesses make informed business decisions via generating insights from data, but these days, he is mostly focused on ML Research and building ML products.