Introduction to ML Deployment: Flask, Docker & Locust

You've spent a lot of time on EDA, carefully crafted your features, tuned your model for days and finally have something that performs well on the test set. Now, my friend, we need to deploy the model. After all, any model that stays in the notebook has a value of zero, regardless of how good it is. It might feel overwhelming to learn this part of the data science workflow, especially if you don't have a lot of software engineering experience. Fear not, this post's main purpose is to get you started by introducing one of the most popular frameworks for deployment in Python -- Flask.