Personalized Fitness Guidance: Leveraging AI and NLP in Chatbot Development

Abstract

This paper describes the design and development of an AI-powered fitness chatbot using NLP techniques to promote fitness. A conversational agent offering help and advice on exercise regimens, diets, and anything exercise/fitness related. The proposed chatbot uses this approach with a neural network from the Keras library, with Dense layers that use ReLU for essential patterns and Softmax for categorizing intents. Tokenizing and stemming with a Bag of Words (BoW) model match user queries with the intents Further, SpaCy increases response effectiveness through linguistic similarity. It uses Streamlit for the front-end to create an easily understandable user interface. This paper discusses how the frameworks of AI, ML, and NLP could complement each other to better improve the impact and convenience of personalized fitness consultations and the help of professionals.