Most people memorize CNN equations without truly understanding what the convolution operation is actually doing.

Here's what happens during a CNN forward pass in under 60 seconds:

🔹 Kernel (Filter) Setup:
A 3 × 3 kernel (filter) slides across the input matrix.

🔹 Element-Wise Multiplication:
At each position, the kernel multiplies its weights with the overlapping input values and sums the results to produce a single scalar output (z₁, z₂, z₃, z₄).

🔹 Stride:
With a stride of 2, the kernel moves two steps horizontally and vertically, creating a compressed 2 × 2 feature map.

🔹 Flattening & Prediction:
The feature map is flattened into a 1D vector, which is then passed through the remaining network layers to generate the final prediction (ŷ). This prediction is used to compute the loss (L).

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