* A multilayer perceptron is a type of neural network which has many layers of perceptron stacked on top of each other.
* Mathematically, multilayer perceptron are capable of learning any mapping function and have been proven to be a universal approximation algorithm.
* Single layer perceptron only learn linear patterns, while multilayer perceptron can learn complex relationships. This predictive capability comes from the multi-layered structure of the network, so that the features can be combined into higher-order features.
