The Main objective of this project is to implement a Chatbot using Deep Learning and Natural Language Processing. The Chatbot is implemented using a Seq2Seq model which is made up of 2 Recurrent Neural Networks (RNN’s) namely the Encoder Recurrent Neural Network and the Decoder Recurrent Neural Network. The cell used in the RNN is LSTM (Long Short Term Memory). The Seq2Seq model is given a question in embedded form and its job is to correctly answer the question given as input. It uses the dataset of Cornell Movie Corpus data for training as well as testing where conversations are given in question and answer format. This dataset can be trained using the Seq2Seq model. The program code has been implemented and written in ‘Python’.
Reference: Deep Learning and NLP A-Z, Udemy