Building Data Apps with Streamlit: Create Dynamic Dashboards, Machine Learning Workflows, and AI Chatbots with Streamlit and Python

Turn Python Scripts into Interactive AI-Powered Apps with Streamlit

KEY FEATURES

● Build complete Streamlit apps from data exploration to deployment

● Integrate ML models and AI chatbots into interactive Python apps

● Master caching, state management, cloud deployment, and multipage architecture

DESCRIPTION

Streamlit has transformed how developers present data science and machine-learning work by making it effortless to turn Python scripts into interactive web applications. Building Data Apps with Streamlit provides a complete, hands-on roadmap to creating professional, production-ready apps using Streamlit’s fast, intuitive, and Pythonic framework.

You begin with Streamlit’s architecture, layout system, and component ecosystem, learning how to build clean, scalable apps with widgets, callbacks, caching, and session state. The book then guides you through handling secrets, managing configurations, working with APIs and databases, and building multipage workflows that feel polished and responsive.

By the end, you will build a full Streamlit solution that analyzes datasets, trains machine-learning models, and powers an AI chatbot using Google Gemini. With dedicated chapters on testing, optimization, and cloud deployment, this book equips you with the confidence and skills to create, iterate, and share high-quality Streamlit applications that bring your data and ideas to life.

WHAT WILL YOU LEARN

● Build interactive data apps using Streamlit’s core components

● Manage session state, caching, themes, and configurations effectively

● Connect apps to APIs, databases, and cloud services

● Integrate machine-learning workflows into Streamlit interfaces

● Create and deploy an AI chatbot using Google Gemini

● Test, deploy, and maintain Streamlit apps on the cloud

WHO IS THIS BOOK FOR?

This book is exclusively designed for data scientists, analysts, and Python developers who want to transform their work into interactive applications without learning traditional web frameworks. A basic understanding of Python and data manipulation with Pandas is recommended, but no prior web development experience is required.This book is exclusively designed for data scientists, analysts, and Python developers who want to transform their work into interactive applications without learning traditional web frameworks. A basic understanding of Python and data manipulation with Pandas is recommended, but no prior web development experience is required.

TABLE OF CONTENTS

1. Introduction to Streamlit

2. Setting Up the Development Environment

3. Creating and Deploying Your First Streamlit App

4. Exploring Streamlit’s Flow and Architecture

5. Persisting Data and State Across App Reruns

6. Exploring Streamlit’s Page Elements

7. Widget Keys and Callbacks

8. Introduction to Streamlit Caching and Connections

9. Managing Secrets in Streamlit

10. Advanced App Management Concepts

11. App Configuration Options

12. Building Multipage Streamlit Apps

13. Testing Streamlit Apps

14. Building a Data Analysis Streamlit App

15. Building a Machine Learning Streamlit App

16. Building a Chatbot on Streamlit

Index