Details zum E-Book

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

François Voron

E-book
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 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.
  • 1. Python Development Environment Setup
  • 2. Python Programming Specificities
  • 3. Developing RESTful API with FastAPI
  • 4. Managing pydantic Data Models in FastAPI
  • 5. Dependency Injections 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 NumPy and Pandas
  • 12. Training Machine Learning Models with scikit-learn
  • 13. Creating an Efficient Prediction API Endpoint with FastAPI
  • 14. Implement a Real-Time Face Detection System Using WebSockets with FastAPI and OpenCV
  • Titel: Building Data Science Applications with FastAPI. Develop, manage, and deploy efficient machine learning applications with Python
  • Autor: François Voron
  • Originaler Titel: Building Data Science Applications with FastAPI. Develop, manage, and deploy efficient machine learning applications with Python
  • ISBN: 9781801074186, 9781801074186
  • Veröffentlichungsdatum: 2021-10-08
  • Format: E-book
  • Artikelkennung: e_2a95
  • Verleger: Packt Publishing