Various steps Involved in Building Machine Learning Pipeline

Oftentimes in machine learning, there is a confusion about how to build a scalable and robust models which can be deployed in real-time. The thing that mostly complicates this is the lack of knowledge about the overall workflow in machine learning. Understanding the various steps in machine learning workflow can be especially handy for data scientists or machine learning engineers as it saves a considerable amount of time and effort in the long run. In this article, we will be going over the steps that are usually involved in building a machine learning system. Having a good understanding of the principles needed to build a high-level design of an AI system is useful so that one could allocate their time and resources to complete each part of the puzzle before coming up with a robust high-performance model that is put to production.