How to Use FastAPI for Machine Learning

FastAPI is gaining popularity among data scientists for building machine learning APIs. It allows quick development of backend services using Python decorators and type hints. Key benefits include fast development, automatic documentation generation, easy testing, and simple deployment. The article demonstrates how to use FastAPI to create an API for a penguin species prediction model and an image classification model. It covers setting up the project, handling requests with query parameters, using lifespan events to manage model setup, and implementing background tasks for model retraining. PyCharm Professional is recommended for easier FastAPI development.