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Getting Started with Streamlit for Data Science

You're reading from   Getting Started with Streamlit for Data Science Create and deploy Streamlit web applications from scratch in Python

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Product type Paperback
Published in Aug 2021
Publisher Packt
ISBN-13 9781800565500
Length 282 pages
Edition 1st Edition
Languages
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Author (1):
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Tyler Richards Tyler Richards
Author Profile Icon Tyler Richards
Tyler Richards
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Creating Basic Streamlit Applications
2. Chapter 1: An Introduction to Streamlit FREE CHAPTER 3. Chapter 2: Uploading, Downloading, and Manipulating Data 4. Chapter 3: Data Visualization 5. Chapter 4: Using Machine Learning with Streamlit 6. Chapter 5: Deploying Streamlit with Streamlit Sharing 7. Section 2: Advanced Streamlit Applications
8. Chapter 6: Beautifying Streamlit Apps 9. Chapter 7: Exploring Streamlit Components 10. Chapter 8: Deploying Streamlit Apps with Heroku and AWS 11. Section 3: Streamlit Use Cases
12. Chapter 9: Improving Job Applications with Streamlit 13. Chapter 10: The Data Project – Prototyping Projects in Streamlit 14. Chapter 11: Using Streamlit for Teams 15. Chapter 12: Streamlit Power Users 16. Other Books You May Enjoy

What this book covers

Chapter 1, An Introduction to Streamlit, teaches the very basics of Streamlit by creating your first app.

Chapter 2, Uploading, Downloading, and Manipulating Data, looks at data; data apps need data! We'll learn how to use data efficiently and effectively in production applications.

Chapter 3, Data Visualization, teaches how to use all your favorite Python visualization libraries in Streamlit apps. There's no need to learn new visualization frameworks!

Chapter 4, Using Machine Learning with Streamlit, covers machine learning. Ever wanted to deploy your new fancy machine learning model in a user-facing app in hours? Start here for in-depth examples and tips. 

Chapter 5, Deploying Streamlit with Streamlit Sharing, looks at the one-click deploy feature that Streamlit comes with. We'll learn how to remove friction in the deployment process here! 

Chapter 6, Beautifying Streamlit Apps, looks at the features that Streamlit is chock-full of to make gorgeous web apps. We'll learn all the tips and tricks in this chapter. 

Chapter 7, Exploring Streamlit Components, teaches how to leverage the thriving developer ecosystem around Streamlit through open source integrations called Streamlit Components. Just like LEGO, only better. 

Chapter 8, Deploying Streamlit Apps with Heroku and AWS, teaches how to deploy your Streamlit applications using AWS and Heroku as an alternative to Streamlit Sharing. 

Chapter 9, Improving Job Applications with Streamlit, will help you to prove your data science chops to employers using Streamlit apps through everything from apps for resume building to apps for take-home sections of interviews.

Chapter 10, The Data Project – Prototyping Projects in Streamlit, covers making apps for the Streamlit community and others, which is both fun and educational. We'll walk through some examples of projects and you'll learn how to start your own. 

Chapter 11, Using Streamlit for Teams, teaches how to deploy private Streamlit repositories and enforce user authentication using the Streamlit product Streamlit for Teams.

Chapter 12, Streamlit Power Users, provides more information on Streamlit, which is already extensively used for such a young library. Learn from the best with in-depth interviews with the Streamlit founder, data scientists, analysts, and engineers.

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