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So you first issue is data. For any problem you would probably need a sizable training dataset.

Hence, your idea should come after the data, not before.

In this case, I would suggest going to companies that already have data (for example support tickets), which they do not use.

After you have data, I would use auto ml.

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But you would need a company to give you data with nothing visible on return. Do you think a company would do that?

Yes. For example, if your problem is important for construction companies, than they will give you data to solve it (otherwise, how would they solve it). In return, they will get to use your models.

In any rate, unless you have a dataset of your own, the ML part does not matter.

I think that any ML project today, it more of a solution engineering type project, and not a product.

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