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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

Gerard Bentley

Tyler: Hey, Gerard! Let’s get started, I was wondering if you could give us a bit about your background. What do you do for work? What got you started in the data world?

Gerard: Right now, I’m working on backend web services at a startup called Sensible Weather. We sell an insurance guarantee against bad weather, a new product in the climate tech space. I haven’t gotten a lot of time to use Streamlit here, but I use it for a couple of things internally that haven’t completely been deployed yet.

Previously, I worked at a mortgage company, doing mostly batch ETL work, where I got a bit of exposure to data science and predictive models in finance. There, it was fun to build something internal in Streamlit to visualize what would happen if a person’s credit score were higher, or if they put more principal down, etc. Before Streamlit we didn’t have a tool to answer those questions quickly.

Tyler: So, you were mostly focused...

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