Streamlit for Data Science - Second Edition : Create interactive data apps in Python

Tyler Richards

ISBN 10: 180324822X / ISBN 13: 9781803248226

Published by Packt Publishing, 2023

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - An easy-to-follow and comprehensive guide to creating data apps with Streamlit, including how-to guides for working with cloud data warehouses like Snowflake, using pretrained Hugging Face and OpenAI models, and creating apps for job interviews.Key Features:Create machine learning apps with random forest, Hugging Face, and GPT-3.5 turbo modelsGain an insight into how experts harness Streamlit with in-depth interviews with Streamlit power usersDiscover the full range of Streamlit's capabilities via hands-on exercises to effortlessly create and deploy well-designed appsBook Description:If you work with data in Python and are looking to create data apps that showcase ML models and make beautiful interactive visualizations, then this is the ideal book for you. Streamlit for Data Science, Second Edition, shows you how to create and deploy data apps quickly, all within Python. This helps you create prototypes in hours instead of days!Written by a prolific Streamlit user and senior data scientist at Snowflake, this fully updated second edition builds on the practical nature of the previous edition with exciting updates, including connecting Streamlit to data warehouses like Snowflake, integrating Hugging Face and OpenAI models into your apps, and connecting and building apps on top of Streamlit databases. Plus, there is a totally updated code repository on GitHub to help you practice your newfound skills.You'll start your journey with the fundamentals of Streamlit and gradually build on this foundation by working with machine learning models and producing high-quality interactive apps. The practical examples of both personal data projects and work-related data-focused web applications will help you get to grips with more challenging topics such as Streamlit Components, beautifying your apps, and quick deployment.By the end of this book, you'll be able to create dynamic web apps in Streamlit quickly and effortlessly.What You Will Learn:Set up your first development environment and create a basic Streamlit app from scratchCreate dynamic visualizations using built-in and imported Python librariesDiscover strategies for creating and deploying machine learning models in StreamlitDeploy Streamlit apps with Streamlit Community Cloud, AWS, and HerokuIntegrate Streamlit with Hugging Face, OpenAI, and SnowflakeBeautify Streamlit apps using themes and componentsImplement best practices for prototyping your data science work with StreamlitWho this book is for:This book is for data scientists and machine learning enthusiasts who want to get started with creating data apps in Streamlit. It is terrific for junior data scientists looking to gain some valuable new skills in a specific and actionable fashion and is also a great resource for senior data scientists looking for a comprehensive overview of the library and how people use it. Prior knowledge of Python programming is a must, and you'll get the most out of this book if you've used Python libraries like Pandas and NumPy in the past.

Seller Inventory # 9781803248226

Bibliographic Details

• Title: Streamlit for Data Science - Second Edition : Create interactive data apps in Python
• Publisher: Packt Publishing
• Publication Date: 2023
• Language: English
• ISBN 10: 180324822X
• ISBN 13: 9781803248226
• Binding: Taschenbuch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 235W x 191H x 17D millimeters 235 millimeters width by 191 millimeters height by 17 millimeters depth
• Weight: 564 grams

About this title

Synopsis

An easy-to-follow and comprehensive guide to creating data apps with Streamlit, including how-to guides for working with cloud data warehouses like Snowflake, using pretrained Hugging Face and OpenAI models, and creating apps for job interviews.

Key Features

• Create machine learning apps with random forest, Hugging Face, and GPT-3.5 turbo models
• Gain an insight into how experts harness Streamlit with in-depth interviews with Streamlit power users
• Discover the full range of Streamlit’s capabilities via hands-on exercises to effortlessly create and deploy well-designed apps

Book Description

If you work with data in Python and are looking to create data apps that showcase ML models and make beautiful interactive visualizations, then this is the ideal book for you. Streamlit for Data Science, Second Edition, shows you how to create and deploy data apps quickly, all within Python. This helps you create prototypes in hours instead of days!

Written by a prolific Streamlit user and senior data scientist at Snowflake, this fully updated second edition builds on the practical nature of the previous edition with exciting updates, including connecting Streamlit to data warehouses like Snowflake, integrating Hugging Face and OpenAI models into your apps, and connecting and building apps on top of Streamlit databases. Plus, there is a totally updated code repository on GitHub to help you practice your newfound skills.

You'll start your journey with the fundamentals of Streamlit and gradually build on this foundation by working with machine learning models and producing high-quality interactive apps. The practical examples of both personal data projects and work-related data-focused web applications will help you get to grips with more challenging topics such as Streamlit Components, beautifying your apps, and quick deployment.

By the end of this book, you'll be able to create dynamic web apps in Streamlit quickly and effortlessly.

What you will learn

• Set up your first development environment and create a basic Streamlit app from scratch
• Create dynamic visualizations using built-in and imported Python libraries
• Discover strategies for creating and deploying machine learning models in Streamlit
• Deploy Streamlit apps with Streamlit Community Cloud, Hugging Face Spaces, and Heroku
• Integrate Streamlit with Hugging Face, OpenAI, and Snowflake
• Beautify Streamlit apps using themes and components
• Implement best practices for prototyping your data science work with Streamlit

Who this book is for

This book is for data scientists and machine learning enthusiasts who want to get started with creating data apps in Streamlit. It is terrific for junior data scientists looking to gain some valuable new skills in a specific and actionable fashion and is also a great resource for senior data scientists looking for a comprehensive overview of the library and how people use it. Prior knowledge of Python programming is a must, and you’ll get the most out of this book if you’ve used Python libraries like Pandas and NumPy in the past.

Table of Contents

1. An Introduction to Streamlit
2. Uploading, Downloading, and Manipulating Data
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

About the Author

Tyler Richards is a senior data scientist at Snowflake, working on a variety of Streamlit-related projects. Before this, he worked on integrity as a data scientist for Meta and non-profits like Protect Democracy. While at Facebook, he launched the first version of this book and subsequently started working at Streamlit, which was acquired by Snowflake early in 2022.