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Reason you need an education in this theory is twofold. How to fix something that is broken in limited time? How to assure this model is reliable? To confidently answer this from a place of reason derived from theory is going to be the real value.

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Sure, but it's a continuum, not a binary dichotomy. Just like you can do more with your car if you have degrees in mechanical engineering and fluid dynamics, but a person with nothing but a high-school diploma can upgrade a camshaft.

The point is, you can do a lot of very useful things with ML, without needing the entirety of the theoretical underpinnings. Of course you can't do everything but not everybody needs to be able to do everything.

So as I said you can copy what others do. That is fine, but you don't k ow deep learning, you know how to apply it based on examples, which is is fine for a lot of things.

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