Building Data Apps with Streamlit Create Dynamic Dashboards, Machine Learning Workflows | 152.93 MB
Title: Building Data Apps with Streamlit: Create Dynamic Dashboards, Machine Learning Workflows, and AI Chatbots with Streamlit and Python
Author: Siddhant Sadangi
Category: Nonfiction, Computers, Database Management, Data Processing, Advanced Computing, Artificial Intelligence, Programming, Programming Languages
Language: English | 334 Pages | ISBN: 9349887843
Description:
Turn Python Scripts into Interactive AI-Powered Apps with Streamlit
Book 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.
Table of Contents
Turn Python Scripts into Interactive AI-Powered Apps with Streamlit
Book 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.
Table of Contents
- Introduction to Streamlit
- Setting Up the Development Environment
- Creating and Deploying Your First Streamlit App
- Exploring Streamlit’s Flow and Architecture
- Persisting Data and State Across App Reruns
- Exploring Streamlit’s Page Elements
- Widget Keys and Callbacks
- Introduction to Streamlit Caching and Connections
- Managing Secrets in Streamlit
- Advanced App Management Concepts
- App Configuration Options
- Building Multipage Streamlit Apps
- Testing Streamlit Apps
- Building a Data Analysis Streamlit App
- Building a Machine Learning Streamlit App
- Building a Chatbot on Streamlit
Index
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