text and sequences this covers preprocessing text data into useful representations working with recurrent neural networks using convnets for sequence processing this explores deep-learning models that can process text (understood as sequences of word or sequences of characters)timeseriesand sequence data in general the two fundamental deep-learning algorithms for sequence processing are recurrent neural networks and convnetsthe one-dimensional version of the convnets that we covered in the previous we'll discuss both of these approaches in this applications of these algorithms include the followingdocument classification and timeseries classificationsuch as identifying the topic of an article or the author of book timeseries comparisonssuch as estimating how closely related two documents or two stock tickers are licensed to