recurrent neural networks predictions are to be made is in the form of sequence (series of entities where the order is importantexamples of sequence data include timeseriesnatural language processingspeech analysisetc figure - demonstrates how regular rnn unfolds (across timeto form recurrent neural network in the following sectionwe will explore the basics of an rnn leveraging figure - regular rnn unfolded (source deep learning www deeplearningbook org/contents/rnn htmllet' start by describing the moving parts of an rnn firstwe introduce some notation we will assume that the input consists of sequence of entities ( ) ( ) (tcorresponding to this inputwe need to produce either sequence ( ) ( ) (tor just one output for the entire input sequence (or sequence with different lengthan rnn of different architecture would provide solution to different use case figure - demonstrates the types of rnn based on the input and output length