Streamlit for Data Science: Create interactive data apps in Python
Author:Tyler Richards (Author), Adrien Treuille (Author)
Publisher finelybook 出版社: Packt Publishing
Publication Date 出版日期: 2023-09-29
Edition 版本: 2nd
Language 语言: English
Print Length 页数: 300 pages
ISBN-10: 180324822X
ISBN-13: 9781803248226
Book Description
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
- An Introduction to Streamlit
- Uploading, Downloading, and Manipulating Data
- Data Visualization
- Machine Learning and AI with Streamlit
- Deploying Streamlit with Streamlit Community Cloud
- Beautifying Streamlit Apps
- Exploring Streamlit Components
- Deploying Streamlit Apps with Hugging Face and Heroku
- Connecting to Databases
- Improving Job Applications with Streamlit
- The Data Project – Prototyping Projects in Streamlit
- Streamlit Power Users
Editorial Reviews
Review
“Streamlit for Data Science teaches you how to master this new superpower. You start by creating a basic analysis and work your way up to complete Streamlit apps with fancy graphics and interactive machine-learning models. You even learn how to use LLMs like OpenAI’s GPT series! This book will turn you into a Streamlit sorcerer.”
—
Adrien Treuille, Streamlit Co-Founder
“The second edition of Streamlit for Data Science is a great resource for anyone interested in building data apps with Python. The author takes us through all the necessary steps to build fully functional and elegant web applications in a matter of minutes. With the suggestions from the book, we can learn how to demonstrate our knowledge and ability to solve programming/data science tasks and present them in an interactive and comprehensive way.”
—
Eryk Lewinson
Author of Python For Finance Cookbook
Data Scientist
“This book will help you to build new apps right in the first few pages, and soon enough, you will be doing more complex apps with that beautiful package. I can say that Streamlit is one of my favorite modules in Python, and I love learning more about it, great book.”
Gustavo R Santos, Data Scientist at Food Lion, Author of Data Wrangling with R
“This book comprehensively covers Streamlit, from fundamental concepts to advanced topics like cloud deployment and custom component integration. A highlight for me was the section on creating interactive maps with Streamlit-folium, which aligns with my work in geospatial data exploration. The book caters to Streamlit newcomers and seasoned users, offering valuable insights.”
Robin Cole PhD
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.
没有下载链接？
已更新