Asian Journal of Advances in Research

Deep learning techniques which implement deep neural networks became popular due to the increase of high-performance computing facility. Deep learning achieves higher power and flexibility due to its ability to process a large number of features when it deals with unstructured data. Deep learning algorithm passes the data through several layers; each layer is capable of extracting features progressively and passes it to the next layer. Initial layers extract low-level features, and succeeding layers combines features to form a complete representation. Chatbot is referred as learning and assistant tool. It is artificially created with the help of neural network in deep learning model. Chatbot is capable enough to interact with the users in the form of text or speech. This paper focuses on the development of chatbot using the open source framework called rasa. Chatbot is a conversational bot which is going to use of natural language processing and mimic the conversation with customer or the users. Rasa has two important component rasa nlu and rasa nlu core. These two are considered as the building block of rasa chatbot. In this article interactive learning and implementation details are tested in anaconda framework. For the implementation purpose rasa 2.0 is used.