The neural network is typically a set size once it's created. You'd have to create a network big enough for your data-set.
How many neurons would a network have after a training of 100k small images?
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Is there any way to estimate how big the neural network would be after training session of 100,000 unlabeled images for unsupervised learning (like in STL-10 dataset: 96x96 pixels and color)?
Not the storage space (because this could vary I guess based on the implementation), but specifically how many neurons it could have. It could be an estimate (e.g. in thousand, millions). If it depends, then on what? Are there any figures that can be estimated?
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