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Streamlit for Data Science

You're reading from   Streamlit for Data Science Create interactive data apps in Python

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781803248226
Length 300 pages
Edition 2nd 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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Table of Contents (15) Chapters Close

Preface 1. An Introduction to Streamlit 2. Uploading, Downloading, and Manipulating Data FREE CHAPTER 3. Data Visualization 4. Machine Learning and AI with Streamlit 5. Deploying Streamlit with Streamlit Community Cloud 6. Beautifying Streamlit Apps 7. Exploring Streamlit Components 8. Deploying Streamlit Apps with Hugging Face and Heroku 9. Connecting to Databases 10. Improving Job Applications with Streamlit 11. The Data Project – Prototyping Projects in Streamlit 12. Streamlit Power Users 13. Other Books You May Enjoy
14. Index

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! You’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, Machine Learning and AI 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, including working with Hugging Face and OpenAI models.

Chapter 5, Deploying Streamlit with Streamlit Community Cloud, looks at the one-click deploy feature that Streamlit comes with. You’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. You’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 Hugging Face and Heroku, teaches how to deploy your Streamlit applications using Hugging Face and Heroku as an alternative to Streamlit Community Cloud.

Chapter 9, Connecting to Databases, will help you add data from production databases into your Streamlit apps, which expands the possible apps you can make.

Chapter 10, 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 11, The Data Project – Prototyping Projects in Streamlit, covers making apps for the Streamlit community and others, which is both fun and educational. You’ll walk through some examples of projects and learn how to start your own.

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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