The Ultimate Guide: Challenges of Machine Learning Model Deployment

Motivation

“Machine learning model deployment is easy”

This is a myth that I’ve heard so many times. As a data scientist with an engineering background, I also had this point of view until actually developed a machine learning deployment (or MLOps) project. Technically, deploying a machine learning(ML) model could be very simple: start a server, create an ML inference API, and apply the API to an existing application. Unfortunately, this workflow is so easy to come up that people …

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