A couple of questions about ML prediction

[Derek_N]

@tony (I hope it is OK to ping you directly - you seem to be the ML guy?)

1: Does training continue if I log out? I uploaded the Iris dataset (150 rows, 4 columns) an hour or so ago and it is still training. I can imagine that a larger dataset will take many days (of course depending on many variables)

2: Is there a public doc describing training optimzation available? Eg shows me options/ benefits for feature scaling/ normalization?

3: Would you describe the algorithm under the hood as a production ready ML? Or maybe a ‘novelty’ implementation demonstrating how other Google Cloud services can be integrated with AppSheet?

4: I’m excited by the possibilities that ‘democratized’ ML apps can bring to businesses - especially integration with other Cloud ML services in the future. Would you say that the current implementation is ‘fast enough’ for training. Or would it be better for a dev to train their own models on another (faster?) platform and then go down the traditional code app path?

5: I’m a ML newbie so I don’t have any specific use cases in mind. I imagine that once I get my head around the tech I will be seeing opportunities everywhere

Thanks and cheers