Creating an Efficient Prediction API Endpoint with FastAPI
In the previous chapter, we introduced the most common data science techniques and libraries largely used in the Python community. Thanks to those tools, we can now build machine learning models that can make efficient predictions and classify data. Of course, we now have to think about a convenient interface so that we can take advantage of their intelligence. This way, microservices or frontend applications can ask our model to make predictions to improve the user experience or business operations. In this chapter, we’ll learn how to do that with FastAPI.
As we’ve seen throughout this book, FastAPI allows us to implement very efficient REST APIs with a clear and lightweight syntax. In this chapter, you’ll learn how to use them as efficiently as possible in order to serve thousands of prediction requests. To help us with this task, we’ll introduce another library, Joblib, which provides tools...
