Getting Started with Streamlit for Data Science
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Section 1: Creating Basic Streamlit Applications
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Free ChapterChapter 1: An Introduction to Streamlit
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Chapter 2: Uploading, Downloading, and Manipulating Data
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Chapter 3: Data Visualization
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Chapter 4: Using Machine Learning with Streamlit
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Chapter 5: Deploying Streamlit with Streamlit Sharing
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Section 2: Advanced Streamlit Applications
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Chapter 6: Beautifying Streamlit Apps
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Chapter 7: Exploring Streamlit Components
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Chapter 8: Deploying Streamlit Apps with Heroku and AWS
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Section 3: Streamlit Use Cases
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Chapter 9: Improving Job Applications with Streamlit
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Chapter 10: The Data Project – Prototyping Projects in Streamlit
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Chapter 11: Using Streamlit for Teams
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Chapter 12: Streamlit Power Users
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About this
book
Streamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes using Python in hours instead of days. Getting Started with Streamlit for Data Science takes a hands-on approach to helping you learn the tips and tricks that will have you up and running with Streamlit in no time.
You'll start with the fundamentals of Streamlit by creating a basic app and gradually build on the foundation by producing high-quality graphics with data visualization and testing machine learning models. As you advance through the chapters, you’ll walk through practical examples of both personal data projects and work-related data-focused web applications, and get to grips with more challenging topics such as using Streamlit Components, beautifying your apps, and quick deployment of your new apps.
By the end of this book, you’ll be able to create dynamic web apps in Streamlit quickly and effortlessly using the power of Python.
- Publication date:
- August 2021
- Publisher
- Packt
- Pages
- 282
- ISBN
- 9781800565500
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