Running Machine Learning Projects: Things to know | by Prashant Mudgal | Oct, 2021 | Towards Data Science

In my experience, ML projects come in all shapes and sizes and vary greatly in their complexity. In the initial 2000/10s, the emphasis was on the model-centric approach which I always found a little bizarre as I heard umpteen times about the fancier models than the results(well, it was a different time and folks used to get awestruck when they would hear ML, AI, DS etc); slowly and steadily the focus has shifted to the result centric approach i.e. use whatever model you can but make use of the data and produce results that are directional, applicable, and coherent.
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