Objective: Reinforce the knowledge acquired in class on the design and programming of neural networks based on the Multilayer Perceptron as a pattern classification tool. Definitions: Convolutional neural networks are a type of artificial neural networks where "neurons" correspond to receptive fields in a very similar way to neurons in the primary visual cortex (V1) of a biological brain. This type of network is a variation of a multilayer perceptron, however, because its application is carried out in two-dimensional matrices, they are very effective for artificial vision tasks, such as in the classification and segmentation of images, among other applications. How to make a convolutional network learn Convolutional Neural Networks, CNN learn to recognize a diversity of objects within images, but for this they need to "train" in advance with a significant amount of "samples" -leave more than 10,000, in this way the neurons of the network will being a...