Ensure Success of Every Machine Learning Project
Last Updated on July 24, 2023 by Editorial Team
Author(s): Mukul Malik
Originally published on Towards AI.
Computational level:
-by geek-and-poke.com under CC-BY-3.0
Machine Learning projects can convince even an atheist that ‘the devil is in the detail’.
Allegedly, a report from Gartner predicted that 85% of the Machine Learning projects will fail. Well, I am not too surprised.
But. There is a cure, as we’ll explore later in this blog.
The problem isn’t that there aren’t enough discussions among and within the teams.
Rather, the problem is that:
people with different backgrounds understand different languagesa common language is almost always absent when defining an ML projectmost discussions soon turn into the game of Chinese whisperambiguity, arising from assumptions, accumulatescompletion within the span of the… Read the full blog for free on Medium.
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