Bøger af François Voron

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 eBookKey Features:Uncover the secrets of FastAPI, including async I/O, type hinting, and dependency injectionLearn to add authentication, authorization, and interaction with databases in a FastAPI backendDevelop real-world projects using pre-trained AI modelsBook 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 programmingGet to grips with basic and advanced concepts of the FastAPI frameworkDeploy a performant and reliable web backend for a data science applicationIntegrate common Python data science libraries into a web backendIntegrate an object detection algorithm into a FastAPI backendBuild a distributed text-to-image AI system with Stable DiffusionAdd metrics and logging and learn how to monitor themWho 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.

This book takes you through the concepts of the FastAPI framework, including its powerful dependency injection system. You'll learn how to build tested and reliable data science apps in Python using FastAPI, train machine learning models, and deploy them to the web.