Building Data Science Applications with FastAPI - Second Edition: Develop, manage, and deploy efficient machine learning applications with Python

Voron, François

Building Data Science Applications with FastAPI - Second Edition: Develop, manage, and deploy efficient machine learning applications with Python

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商品描述

Learn all the features and best practices of FastAPI to build, deploy, and monitor powerful data science and AI apps, like object detection or image generation.
Purchase of the print or Kindle book includes a free PDF eBook

Key Features

  • Uncover the secrets of FastAPI, including async I/O, type hinting, and dependency injection
  • Learn to add authentication, authorization, and interaction with databases in a FastAPI backend
  • Develop real-world projects using pre-trained AI models

Book Description

Building Data Science Applications with FastAPI is the go-to resource for creating efficient and dependable data science API backends. This second edition incorporates the latest Python and FastAPI advancements, along with two new AI projects – a real-time object detection system and a text-to-image generation platform using Stable Diffusion.

The book starts with the basics of FastAPI and modern Python programming. You'll grasp FastAPI's robust dependency injection system, which facilitates seamless database communication, authentication implementation, and ML model integration. As you progress, you'll learn testing and deployment best practices, guaranteeing high-quality, resilient applications.

Throughout the book, you'll build data science applications using FastAPI with the help of projects covering common AI use cases, such as object detection and text-to-image generation. These hands-on experiences will deepen your understanding of using FastAPI in real-world scenarios.

By the end of this book, you'll be well equipped to maintain, design, and monitor applications to meet the highest programming standards using FastAPI, empowering you to create fast and reliable data science API backends with ease while keeping up with the latest advancements.

What you will learn

  • Explore the basics of modern Python and async I/O programming
  • Get to grips with basic and advanced concepts of the FastAPI framework
  • Deploy a performant and reliable web backend for a data science application
  • Integrate common Python data science libraries into a web backend
  • Integrate an object detection algorithm into a FastAPI backend
  • Build a distributed text-to-image AI system with Stable Diffusion
  • Add metrics and logging and learn how to monitor them

Who this book is for

This book is for data scientists and software developers interested in gaining knowledge of FastAPI and its ecosystem to build data science applications. Basic knowledge of data science and machine learning concepts and how to apply them in Python is recommended.

商品描述(中文翻譯)

學習所有 FastAPI 的功能和最佳實踐，以建立、部署和監控強大的數據科學和人工智慧應用程式，例如物體檢測或圖像生成。

購買印刷版或 Kindle 版本的書籍將包含一本免費的 PDF 電子書。

主要特點

- 揭示 FastAPI 的秘密，包括異步 I/O、類型提示和依賴注入
- 學習在 FastAPI 後端中添加身份驗證、授權和與數據庫的交互
- 使用預訓練的人工智慧模型開發真實世界的項目

書籍描述

《使用 FastAPI 構建數據科學應用程式》是創建高效可靠的數據科學 API 後端的首選資源。第二版結合了最新的 Python 和 FastAPI 技術，並新增了兩個人工智慧項目 - 即時物體檢測系統和使用 Stable Diffusion 的文本到圖像生成平台。



本書從 FastAPI 和現代 Python 編程的基礎開始。您將掌握 FastAPI 強大的依賴注入系統，這有助於實現無縫的數據庫通信、身份驗證實現和機器學習模型集成。隨著學習的進展，您將學習測試和部署的最佳實踐，確保高質量、具有彈性的應用程式。



在整本書中，您將使用 FastAPI 構建數據科學應用程式，並通過涵蓋常見的人工智慧應用案例（如物體檢測和文本到圖像生成）的項目來幫助。這些實踐經驗將加深您對在實際情況下使用 FastAPI 的理解。



通過閱讀本書，您將能夠使用 FastAPI 維護、設計和監控應用程式，以符合最高的編程標準，輕鬆創建快速可靠的數據科學 API 後端，並跟上最新的技術進展。

您將學到什麼

- 探索現代 Python 和異步 I/O 編程的基礎知識
- 熟悉 FastAPI 框架的基本和高級概念
- 為數據科學應用程式部署高效可靠的網絡後端
- 將常見的 Python 數據科學庫集成到網絡後端
- 將物體檢測算法集成到 FastAPI 後端
- 使用 Stable Diffusion 構建分佈式文本到圖像人工智慧系統
- 添加指標和日誌，並學習如何監控它們

本書適合對 FastAPI 及其生態系統有興趣的數據科學家和軟體開發人員。建議具備基本的數據科學和機器學習概念以及如何在 Python 中應用它們的知識。

目錄大綱

  1. Python Development Environment Setup
  2. Python Programming Specificities
  3. Developing a RESTful API with FastAPI
  4. Managing Pydantic Data Models in FastAPI
  5. Dependency Injection in FastAPI
  6. Databases and Asynchronous ORMs
  7. Managing Authentication and Security in FastAPI
  8. Defining WebSockets for Two-Way Interactive Communication in FastAPI
  9. Testing an API Asynchronously with pytest and HTTPX
  10. Deploying a FastAPI Project
  11. Introduction to Data Science in Python
  12. Creating an Efficient Prediction API Endpoint with FastAPI
  13. Implementing a Real-Time Object Detection System Using WebSockets with FastAPI
  14. Creating a Distributed Text-to-Image AI System Using the Stable Diffusion Model
  15. Monitoring the Health and Performance of a Data Science System

目錄大綱(中文翻譯)

Python 開發環境設置
Python 編程特點
使用 FastAPI 開發 RESTful API
在 FastAPI 中管理 Pydantic 數據模型
在 FastAPI 中使用依賴注入
數據庫和異步 ORM
在 FastAPI 中管理身份驗證和安全性
在 FastAPI 中定義雙向互動通信的 WebSockets
使用 pytest 和 HTTPX 非同步測試 API
部署 FastAPI 項目
Python 中的數據科學介紹
使用 FastAPI 創建高效的預測 API 端點
使用 FastAPI 實現實時物體檢測系統，使用 WebSockets
使用穩定擴散模型創建分佈式文本到圖像 AI 系統
監控數據科學系統的健康和性能

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