📄️ Convolution
Understanding kernels, filters, and how feature maps are created in Convolutional Neural Networks.
📄️ Pooling
Understanding Max Pooling, Average Pooling, and how they provide spatial invariance.
📄️ Padding
How padding prevents data loss at the edges and controls the output size of convolutional layers.
📄️ Strides
Understanding how the step size of a filter influences spatial dimensions and computational efficiency.