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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 FREE CHAPTER 2. Uploading, Downloading, and Manipulating Data 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

The Data Project – Prototyping Projects in Streamlit

In the previous chapter, we discussed how to create Streamlit applications that are specific to job applications. Another fun application of Streamlit is to try out new and interesting data science ideas and create interactive apps for others. Some examples of this include applying a new machine learning model to an existing dataset, carrying out an analysis of some data uploaded by users, or creating an interactive analysis on a private dataset. There are numerous reasons for making a project like this, such as personal education or community contribution.

In terms of personal education, often, the best way to learn about a new topic is to observe how it actually works by applying it to the world around you or a dataset that you know closely. For instance, if you try to learn how Principal Component Analysis works, you can always learn about it in a textbook or watch someone else apply it to a dataset. However, I have...

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