Python Deep Learning Projects

Convolution

Convolution can be defined as the process of striding a small kernel/filter/array over a target array and obtaining the sum of element-wise multiplication between the kernel and a subset of equal size of the target array at that location.

Consider the following example:

array = np.array([0, 1, 0, 1, 0, 1, 0, 1, 0, 1])kernel = np.array([-1, 1, 0])

Here, you have a target array of length 10 and a kernel of length 3.

When you start the convolution, implement the following steps:

1. The kernel will be multiplied with the subset of the target array within indices 0 through 2. This will be between [-1,1,0] (kernel) and [0,1,0] (from index 0 through to 2 of the target array). The result of this element-wise multiplication will then be ...