Streamlit Essentials

Streamlit Essentials is a comprehensive guide aimed at helping you build interactive data applications using Python. With easy-to-use syntax, it allows developers to quickly build visualizations, dashboards, and machine learning models.

This book is a practical guide to building data science applications using the Streamlit framework. It covers everything from installation to advanced topics like ML integration and deployment. With real-world projects and examples, you will learn how to use Streamlit's widgets, styling, and data visualization tools to create dynamic real-time dashboards, containerize your applications with Docker, securely handle sensitive data, and deploy the applications on leading cloud platforms, all while building practical projects that can be added to enhance your portfolio.

Throughout the book, you will develop the skills needed to turn data insights into interactive visualizations, ensuring your projects are not only functional but also engaging. The focus is hands-on learning, with step-by-step guidance to help you build, optimize, and share your work. By the time you have completed this book, you will be able to confidently deploy applications, showcase your skills through a professional portfolio, and position yourself for success. 

KEY FEATURES  

• Learn how to present data insights quickly and clearly using Streamlit for smoother collaboration between business and tech teams.
• Master Streamlit’s core and advanced features through hands-on projects like product recommenders.
• Build and deploy data applications while exploring over 25 project ideas to enhance your Streamlit skills.
• Explore the Gen AI toolkit to speed up your development cycle from ideation to deployment.

WHAT YOU WILL LEARN

• Understanding of Streamlit's capabilities, from its core functionalities to advanced features.
• Create engaging and informative visualizations using Streamlit's extensive library of charts, graphs, and maps.
• Develop efficiently using time-saving techniques for rapid prototyping and iterative development.
• Optimize app performance with advanced topics like caching, session tracking, and theming.
• Create a compelling portfolio to demonstrate your Streamlit proficiency.

WHO THIS BOOK IS FOR

Whether you are a data scientist, analyst, developer, or business professional, this book will provide you with the knowledge and skills needed to build engaging and informative dashboards, visualizations, and ML models.

1. Introduction to Streamlit
2. Getting Started with Streamlit
3. Exploring Streamlit Widgets
4. Styling and Layouts in Streamlit
5. Data Visualization with Streamlit
6. Streamlit and Machine Learning
7. Advanced Streamlit Concepts
8. Deployment of Streamlit Apps
9. Hands-On Projects: Easy
10. Hands-On Projects: Intermediate
11. Hands-On Projects: Advanced
12. Build and Enhance Your Portfolio
13. Enhancing Streamlit Development with AI Tools
Appendix A: Streamlit Cheat Sheet
Appendix B: Additional Resources and References
Appendix C: Docker 101: Beginner’s Guide to Containers

Surabhi is a data enthusiast with over a decade of experience across various data- focused roles. She holds a Bachelor’s Degree in Computer Science from Amrita Vishwavidyapeetham. She enjoys the challenges and opportunities that come with turning raw data into meaningful insights and creating data-driven solutions that empower business decision-making.

Her background includes a mix of programming languages and tools; her current favorite toolkit includes DBT, Airflow, and Great Expectations, and her go-to language is Python. She has a keen interest in building frameworks to improve and streamline data quality and governance. Currently based in Kuala Lumpur, Surabhi enjoys a good cup of coffee and is an avid reader of epic fantasy novels.