Deep Learning: Common Architectures – srnghn – Medium

This post is designed to be an overview highlighting three of the most common deep learning architectures: Multi-layer Perceptrons, Convolutional Neural Networks and Recurrent Neural Networks. The content in this post is high-level, introducing the main features of each architecture and describing the type of data it tends to be used for. It is complementary to the post Introduction to Deep Learning: What do I need to know…?. The above diagram is a multi-layer perceptron (MLP). An MLP can have many layers but must have at least three: the input, a hidden layer, and the output layer.