Important terminology that you need to know to learn CNN.

CNN: Convolutional neural network. That is a network that has at least one convolutional layer. A typical CNN also includes other types of layers, such as pooling and dense layers.

Convolution: The process of applying a kernel (filter) to an image

Kernel/filter: A matrix that is smaller than the input, used to transform the input into chunks

Padding: Adding pixels of some value, usually 0, around the input image

Pooling The process of reducing the size of an image through downsampling. There are several types of pooling layers. For example, average pooling converts many values into one by taking the average. However, max-pooling is the most common.

Max pooling: A process in which many values are converted into a single value by taking the maximum value from among them.

Stride: the number of pixels to slide the kernel (filter) across the image.

Downsampling: The act of reducing the size of an image