I'm taking a course on Apple's machine learning technologies. I just came across this paragraph:

Turi Create and Create ML are task-specific, rather than model-specific. This means that you specify the type of problem you want to solve, rather than choosing the type of model you want to use. You select the task that matches the type of problem you want to solve, then Turi Create analyzes your data and chooses the right model for the job.

My question is when you select a task like binary image classification, and Create ML / Turi Create selects an appropriate model for you, what models does it have at its disposal. Aren't there MANY models in the market that do this? Did Apple simply pick the one they thought was best?



TuriCreate has several different models implemented. You can either use them specifically or you can use a create method which will analyze your data and pick one of them (not always the same one).

For instance in binary classification (not image) there is support for random forest, decision tree, boosted trees, logistic regression, SVMs and nearest neighbor.

I don't know exactly how it makes the selection, but I imagine it has a lot to do with the dimensions of your data.

  • $\begingroup$ Excellent! Thanks! $\endgroup$ – Martin Muldoon Mar 15 at 13:25

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