What Is the Difference Between CNN and RNN?
What is the Difference Between CNN and RNN? - Towards Data Science
Convolutional Neural Networks and Recurrent Neural Networks are commonly used in ML today. However, they are often used for completely different use cases.Image by AuthorIn machine learning, each type of artificial neural network is tailored to certain tasks. This article will introduce two types of neural networks: convolutional neural networks (CNN) and recurrent neural networks (RNN). Using popular Youtube videos and visual aids, we will explain the difference between CNN and RNN and how they are used in computer vision and natural language processing.What is the Difference Between CNN and RNN?The main difference between CNN and RNN is the ability to process temporal information or data that comes in sequences, such as a sentence for example. Moreover, convolutional neural networks and recurrent neural networks are used for completely different purposes, and there are differences in the structures of the neural networks themselves to fit those different use cases.CNNs employ filters within convolutional layers to transform data. Whereas, RNNs reuse activation functions from other data points in the sequence to generate the next output in a series.