You may wonder why?

In theory, it should be simple to come up with an idea, gather feedback and prototype to get a demo and validate the concept.

However, in reality, the majority of data science and machine learning professionals fail at every step of the process and as a result deliver solutions that rarely achieve production stage or post launch and are of no value whatsoever (do not increase productivity, revenue or simply do not entertain).

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How to effectively define and validate AI/ML Use Cases
1.50 GEEK