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  title: '"My understanding is that [8qg neural nets alrea..."',
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  anchorContext: 'However, this sounds a little bit strange and anti\\-intuitive: do we really need to map everything into such a high\\-dimensional space, in order to just classify 10 different digits? Neural networks seems to be somehow a mimic of brain, but my brain \\(at least mine\\) recognizing a digit does not seems to be relying on almost a thousand discrete features of that specific digit, no need to mention that the size of digits in real life could vary vastly according to multiple factors like distance\\. Do we really need all these features to perform the classification, or can we just first extract less but more pivotal features out the raw image? ',
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  text: 'My understanding is that [8qg neural nets already determine the key features that are important to the decision. The importance of a given feature is represented by the weight on a particular neuron/input-feature.] \n\nSo no we don't need every feature. We just need all features relevant to the decision. So some amount of pre-processing can definitely help.',
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