You Should Be Aware Of These (Common )Deep Learning Terms And Terminologies

Convolutional layer: A convolution is a mathematical term that describes a dot product multiplication between two sets of elements. Therefore a convolutional layer simply houses the convolution operation that occurs between the filters and the images passed through a convolutional neural network. Batch Normalization layer: Batch Normalization is a technique that mitigates the effect of unstable gradients within a neural network through the introduction of an additional layer that performs operations on the inputs from the previous layer. The operations standardize and normalize the input values, after that the input values are transformed through scaling and shifting operations. MaxPooling layer: Max pooling is a variant of sub-sampling where the maximum pixel value of pixels that fall within the receptive field of a unit within a sub-sampling layer is taken as the output.