Note that the search space can be dynamic: here you have a 'for' loop controlled by a hyperparameter, inside which you define new hyperparameters. You could push this to any level (e.g. searching over a connectivity graph for a dynamic number of nodes). Even recursion...
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Tweets like this are why the bookmark feature exists.
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Merci François.
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Coincidently I was thinking today of implementing a bayesian optimization in DL with Hyperopt. Will try Hyperband as well. Thank you Mr. Chollet.
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Just saw it on a
@PyData talk on youtube. -
Is there a link? That would be awesome!
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Ima just pretend I understood all of this.
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What theme is that in studio? Nice pastels......I guess I could go thru them all.
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AWESOME. Default seems like a pure MNIST. Try https://github.com/srohit0/food_mnist … as a challenge. I am pulling my hair
with autoKeras for past 2-3 days to improve the accuracy past 70%. -
Didn't you try transfer learning approach?
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