Getting Started with Streamlit for Data Science

Streamlit is a Python library built to speed up the creation of web applications centered on data. With it, a data scientist can assemble a working prototype within hours rather than the days such work often takes. This guide is organized around practical learning, offering a set of techniques and shortcuts intended to get readers productive with the library quickly.

The book opens with the basics of Streamlit, beginning with a simple app. From there it builds step by step, showing how to produce polished graphics and data visualizations and how to test machine learning models inside an app.

As the chapters progress, the examples become more involved. They cover both personal data projects and data-focused web applications of the kind used at work. The later material turns to more demanding topics: Streamlit Components, making an app look more refined, and deploying a finished app without much delay.

Written for data scientists and machine learning enthusiasts who want to build web apps with Streamlit, the book serves a range of readers. Junior data scientists who want to deploy a first Python machine learning project and strengthen their resume will find it useful, and so will senior practitioners who want to make their data analyses more compelling and interactive. Prior knowledge of Python will help readers follow the concepts covered.