recurrent neural networks the field of natural language processing (nlphas witnessed phenomenal growth with the advent of deep learning lot of this movement can be credited to recurrent neural networks (rnnsand their variants voicebased ai assistantsauto-completion of text in smartphone keyboardsand text-based reviews classified based on sentiments are all problems effectively solved by rnns this begins by exploring the foundational concepts involved with rnns we then explore few variations of the vanilla rnn model that are more suitable for modern computational tasks finallywe will study the practical implementation of an rnn using pytorch on real-world dataset borrowed from our favorite platformkaggle let' get started introduction to rnns recurrent neural networks (rnnsare essentially neural networks that employ recurrencewhich is using information from previous forward pass over the neural network essentiallyall rnns can be described as recurrence relationship rnns are suited forand have been incredibly successful when applied toproblems wherein the input data on which the (cnikhil ketkarjojo moolayil ketkar and moolayildeep learning with python