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

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

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International Edition


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.

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About the Book

Get well-versed with FastAPI features and best practices for testing, monitoring, and deployment to run high-quality and robust data science applications


Key Features:

  • Cover the concepts of the FastAPI framework, including aspects relating to asynchronous programming, type hinting, and dependency injection
  • Develop efficient RESTful APIs for data science with modern Python
  • Build, test, and deploy high performing data science and machine learning systems with FastAPI


Book Description:

FastAPI is a web framework for building APIs with Python 3.6 and its later versions based on standard Python-type hints. With this book, you'll be able to create fast and reliable data science API backends using practical examples.


This book starts with the basics of the FastAPI framework and associated modern Python programming language concepts. You'll then be taken through all the aspects of the framework, including its powerful dependency injection system and how you can use it to communicate with databases, implement authentication and integrate machine learning models. Later, you'll cover best practices relating to testing and deployment to run a high-quality and robust application. You'll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you'll learn how to build data science applications in Python using FastAPI. The book also demonstrates how to develop fast and efficient machine learning prediction backends and test them to achieve the best performance. Finally, you'll see how to implement a real-time face detection system using WebSockets and a web browser as a client.


By the end of this FastAPI book, you'll have not only learned how to implement Python in data science projects but also how to maintain and design them to meet high programming standards with the help of FastAPI.


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
  • Implement a FastAPI dependency to efficiently run a machine learning model
  • Integrate a simple face detection algorithm in a FastAPI backend
  • Integrate common Python data science libraries in a web backend
  • Deploy a performant and reliable web backend for a data science application


Who this book is for:

This Python data science 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.


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Product Details
  • ISBN-13: 9781801079211
  • Publisher: Packt Publishing Limited
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Sub Title: Develop, manage, and deploy efficient machine learning applications with Python
  • Width: 191 mm
  • ISBN-10: 1801079218
  • Publisher Date: 08 Oct 2021
  • Height: 235 mm
  • No of Pages: 426
  • Spine Width: 22 mm
  • Weight: 729 gr


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