HIGHLIGHTS
SUMMARY
Convolutional neural_networks. CNNs refer to a neural_network substantially comprised of ‘convolution` layers that excel at processing grid-like information i.e. images. CNN-based modelling approaches have remained state-of-the-art for processing and classifying images in machine_learning over the decade. Like any other computer-based neural_network architecture, CNNs are comprised of a sequential layers of artificial ‘neurons` that take numerical values as inputs, and then output another numerical value to the next layer which is controlled by ‘learnable` weights and biases (i.e. weights are continually adjusted automatically by the training algorithm . . .
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