Streamlit for Data Science : Create interactive data apps in Python, 2/e (Paperback)

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.

一本易於理解且全面的指南，教你如何使用Streamlit創建數據應用程式，包括使用Snowflake等雲數據倉庫的操作指南，使用預訓練的Hugging Face和OpenAI模型，以及創建求職面試應用程式的方法。

主要特點：
- 使用隨機森林、Hugging Face和GPT-3.5 turbo模型創建機器學習應用程式
- 通過深入訪談Streamlit高級用戶，了解專家如何利用Streamlit
- 通過實踐練習，全面了解Streamlit的功能，輕鬆創建和部署設計良好的應用程式

書籍描述：
如果你在Python中處理數據，並且希望創建展示機器學習模型並製作美觀互動可視化的數據應用程式，那麼這本書非常適合你。《Streamlit for Data Science, Second Edition》將教你如何快速創建和部署數據應用程式，全部在Python中完成。這將幫助你在幾小時內創建原型，而不是幾天！

這本全面更新的第二版由一位經驗豐富的Streamlit用戶和Snowflake的高級數據科學家撰寫，基於上一版的實用性，增加了一些令人興奮的更新，包括將Streamlit連接到像Snowflake這樣的數據倉庫，將Hugging Face和OpenAI模型集成到應用程式中，以及連接和構建基於Streamlit數據庫的應用程式。此外，還有一個完全更新的GitHub代碼庫，幫助你練習新學到的技能。

你將從Streamlit的基礎知識開始，逐步建立在此基礎上，使用機器學習模型並創建高質量的互動應用程式。個人數據項目和工作相關的數據導向Web應用程式的實際示例將幫助你掌握更具挑戰性的主題，如Streamlit組件、美化應用程式和快速部署。

通過閱讀本書，你將能夠快速而輕鬆地在Streamlit中創建動態Web應用程式。

你將學到什麼：
- 設置第一個開發環境，從頭開始創建基本的Streamlit應用程式
- 使用內置和導入的Python庫創建動態可視化
- 探索在Streamlit中創建和部署機器學習模型的策略
- 使用Streamlit Community Cloud、Hugging Face Spaces和Heroku部署Streamlit應用程式
- 將Streamlit與Hugging Face、OpenAI和Snowflake集成
- 使用主題和組件美化Streamlit應用程式
- 實施用於原型設計數據科學工作的最佳實踐

本書適合對Streamlit中創建數據應用程式感興趣的數據科學家和機器學習愛好者。對於希望以具體可行的方式獲得寶貴新技能的初級數據科學家來說，這本書非常棒，同時也是高級數據科學家瞭解該庫及其使用方式的全面概述的重要資源。必須具備Python編程的基礎知識，如果你之前使用過Pandas和NumPy等Python庫，你將能從本書中獲得最大的收益。

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

1. Streamlit 簡介


2. 上傳、下載和操作資料


3. 資料視覺化


4. 使用 Streamlit 進行機器學習和人工智慧


5. 使用 Streamlit Community Cloud 部署 Streamlit


6. 美化 Streamlit 應用程式


7. 探索 Streamlit 元件


8. 使用 Hugging Face 和 Heroku 部署 Streamlit 應用程式


9. 連接資料庫


10. 使用 Streamlit 提升求職申請


11. 資料專案 - 在 Streamlit 中進行原型開發


12. Streamlit 高級使用者