Brief intro to recurrent neural networks
Note: This post is meant to be a brief and intuitive summary of recurrent neural networks. I have adapted this material from the Coursera deep learning course. The value I hope to add here is that I have attempted to summarize the information in a way that is easy (hopefully) to understand, and can be used as reference or refresher material for the future. Part 1: Recurrent Neural Networks: Recurrent neural networks are a class of neural networks where the nodes/neurons form a directed graph along a sequence. They are very effective at tasks such as Natural Language Processing because they have a "memory," in other words they can receive context from previous inputs. They can take in input one at a time, and can pass information from one node to the next via hidden activation layers. This information serves as the "memory" or "context" layer of the network, which can be used in conjunction as more new input is being processed. RNN Cell: ...