Python chatbot – what is it?
Python chatbotare one of the solutions used for automation. Bots are used in many fields, such as fintech, e-commerce, government and many more. Most chatbots use natural language processing methods, and in many cases also machine learning methods. Python chatbot example: they can be divided into groups, depending on topics such as complexity, use or privacy. The most popular taxonomy divides chatbots into three groups: rule-based chatbots, search-based chatbots, generative chatbots.
Python chatbot example – rules and search
Python chatbot based on rules rely on a list of questions and matching answers. It can be a loose list of questions or a simple scenario with such questions in which the user is asked questions one by one until chatbot receives all the information needed to return a valuable answer. These may be chatbots making flight reservations, asking for the date of departure, destination and place of departure. After the response chatbot can ask for more to filter out the best fit, such as the number of stops, departure or arrival time, etc. It is simple and we do not need to use any machine learning methods, and in most cases no natural language processing is required. Chatbots based on searching should rely on machine learning and vectorization of words. Words are vectorized because machine learning methods use numbers to predict. There are several methods that can be used for vectorization. The vectorization result allows you to place each word in the function space. In many cases, the vector consists of more values.