Resilient Backpropagation (Rprop): The Robust Optimization Algorithm for Training Deep Neural Networks
Resilient Backpropagation (Rprop) is a popular optimization algorithm used in training artificial neural networks. The algorithm was first introduced by Martin Riedmiller and Heinrich Braun in 1993.
Multi-Layer Perceptron (MLP): A Basic Understanding
Multi Layer Perceptron (MLP) is a type of artificial neural network that is widely used for various machine learning tasks such as classification and regression. It is called a multi-layered perceptron because it has many layers of nodes (known as artificial neurons) that connect to each other.