A Convolutional Neural Networks (CNN) is a form of artificial neural networks in machine learning. We will first inspect the CNN, and then move on to the RNN. A CNN has proven to be very reliable and accurate at image classification, and is used in IoT deployments for visual recognition, especially in security systems. It is a good starting point to understand the process and mathematics behind any artificial neural network. Any data that can be represented as a fixed bitmap (say, a 1024 x 768 pixel image in three planes). A CNN attempts to classify an image to a label (for example, cat, dog, fish, bird) based on an additive set of decomposable features. The primitive features that compose image content are built up from small sets of horizontal lines, vertical lines, curves, shades, gradient directions, and so on.