Elements of a Machine Learning System
Data and algorithms are crucial for machine learning systems, but they are far from sufficient. Algorithms are the smallest part of a production machine learning system. Machine learning systems also require data, infrastructure, monitoring, and storage to function efficiently. For a large-scale machine learning system, we need to ensure that we can include a good user interface or package model in microservices.
In modern software systems, combining all necessary elements requires different professional competencies – including machine learning/data science engineering expertise, database engineering, software engineering, and finally interaction design. In these professional systems, it is more important to provide reliable results that bring value to users rather than include a lot of unnecessary functionality. It is also important to orchestrate all elements of machine learning together (data, algorithms, storage, configuration,...
