Machine Learning for Product Managers
Neal Lathia

As a former engineer turned PM, one of the biggest hurdles I’ve had to face is letting go of the implementation specifics.

Taking the maths out of ML is a great example of where the boundary lies between PM (why/what) and engineering/design (how).

As a PM, we’re looking at why we should use ML and what benefits/costs/advantages it offers our business and customers. Let the engineers work out the maths behind it, that’s a problem for them to (enjoyably) solve. 
By only knowing that ML is a thing and that its capable of doing certain things, it stops us from bogged down in the details… This same concept should be applied to any technical discussions, where its our job to know about the mechanics of a product, but not the specifics of how the feature is implemented.

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