We often think that being judgemental is a symbol of arrogance but that's not true everytime , sometimes it have its own benefits.
In 1996 ,David Wolpert gave NFL (No Free Lunch) Theorem for optimizations which stated
"That if you make no assumptions about data , then there is no way to identify which machine learing model works better than others."
For some datsets model A would perform better while for some datasets it won't , given that we make some assumptions about the data.
In real world it's not possible to train all machine learning model and evaluate them . so , we make some rational assumptions about the data to narrow down the choice of models which will perform better on that specific dataset.
Well well well , there is no such use of this theorem in real life , in almost all cases . The author himself rejected the use of this theorem :)
console.log("NFL");