thanks a lot!
New post is up: "Building powerful image classification models using very little data" http://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html …pic.twitter.com/AxgOAvPURr
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Thanks. Twitter will use this to make your timeline better. UndoUndo
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thoughts on how small we can go on training data & still get good (90+) results?
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depends on the problem. With very simple problems (MNIST) you can go down to ~100 samples (10 per class)
End of conversation
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Would you allow me publish a french translation of your article ? Best regards.
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That's fine, as long as you include proper credit attribution and links to the original
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New conversation -
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