ImageNet and Imagenette

Part 1 (2020)
1

I’m currently on Chapter 7 in the book where we are learning about techniques used in State of the art Image Models.

Jeremy mentions about the importance of prototyping on a small dataset if your dataset is large (and thus, why he created Imagenette).

Here’s my question, how exactly do we make a subset of a dataset? And what are the rules to make sure its representative of the rest, such that the trained model will adapt well to the full dataset eventually?

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also curious and I found a related paper: [1906.04887] Using Small Proxy Datasets to Accelerate Hyperparameter Search

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