A Recursive Neural Network is a type of artificial neural network that takes a piece of data, analyzes it, and then uses that analysis to inform how it processes the next piece of data. This process is repeated until all of the data has been analyzed, and the network is able to draw conclusions and make predictions based on the patterns it has identified. Recursive Neural Networks are often used in tasks that require the analysis of complex, hierarchical data structures, such as Natural Language Processing (NLP), image recognition, and computer vision. They are particularly useful for tasks that involve analyzing the relationships between different pieces of data, as they are able to follow the logical structure of the data and identify patterns that may not be apparent to a traditional machine learning algorithm.
