ML systems are both complex and unique. They are complex because they consist of many different components (ML algorithms, data, business logic, evaluation metrics, underlying infrastructure, etc.) and involve many different stakeholders (data scientists, ML engineers, business leaders, users, even society at large). ML systems are unique because they are data dependent, and data varies wildly from one use case to the next.
