Hey, Very much a beginner with tensorflow, but been enjoying it
so far.
Background: response between 0-200, have 43 variables,
regression type problem, data set is over 200k rows
I’ve built a basic sequential model using Keras, and my loss
and validation loss are ideal – I.e validation loss is slightly
above loss, and it looks as it should.
However my actual loss seems quite high, it is converging around
34 and I’d have liked it to be around 20, now because of the
above I’m not sure if this means my data isn’t actually
predictive?!
I have standardised many variables rather than normalised, I’m
not sure if this would make any difference.
Is there anything I could add you think? I don’t think the
data set is lacking particularly woth the dimensions.
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