Building and Deploying a Machine Learning Model API with FastAPI and Docker
Introduction Deploying machine learning models into production is one of the most critical — and often most challenging — steps in the ML lifecycle. While building a high-accuracy model in a Jupyter notebook is rewarding, making that model accessible to applications, users, and other services through a reliable API requires a solid engineering foundation. In…