ABSTRACT
In this study we present "Talk-A-Bot" an advanced Python-based AI Chatbot utilizing machine learning techniques. With a focus on user-friendly interactions, the chatbot employs text preprocessing, LSTM-based response generation, TF-IDF vectorization and cosine similarity. Specifically designed for medical care "Talk-A-Bot" demonstrates proficiency in contextual understanding and response generation, addressing accessibility, information dissemination and symptom assessment. Findings highlight its value as a tool for medical information seekers emphasizing the intersection of technology and healthcare. The chatbot's adaptability to specialized datasets solidifies its role in healthcare contributing to improved communication and accessibility aligning with the goal of enhancing healthcare services through technology.
Keywords: Chatbot, Machine Learning, Python, NLP, NLTK, Algorithms, Token, Data