October 2017
Beginner to intermediate
270 pages
7h
English
Content preview from Machine Learning for Developers
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Subsampling operation (pooling)
The subsampling operation consists of applying a kernel (of varying dimensions) and reducing the extension of the input dimensions by dividing the image into mxn blocks and taking one element representing that block, thus reducing the image resolution by some determinate factor. In the case of a 2 x 2 kernel, the image size will be reduced by half. The most well-known operations are maximum (max pool), average (avg pool), and minimum (min pool). The following image gives you an idea of how to apply a 2 x 2 maxpool kernel, applied to a one-channel 16 x 16 matrix. It just maintains the maximum value of the internal zone it covers:
Now that we have seen this simple mechanism, let's ask ourselves, what's the ...
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