convolutions
Convolutions is applying a filter to an input that results in an activation, such as with convolutional neural networks (cnn)
For ml, a convolution is a linear operation that involves the multiplation of a set of weights with the input
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for convolutional neural networks (cnn)
- the filter is smaller than the input data and is mulitplied by the dot product
- smaller is intentional, allows the filter to be reused across multiple places in the image
- if we design the filter to detect a specific type of feature, then this can be discovered anywhere in the image (aka translation invariance, checking if the feature is present rather than where it was present)
- the filter is smaller than the input data and is mulitplied by the dot product