Building Data Science Applications with FastAPI

Table of Contents

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