Chatbot with Machine Learning: Latest Advancements

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The aim of this chapter is to enhance the conversational skills of a chatbot through the use of machine learning methods. The chatbot is going to be created in a way that it comprehends conversational input and offers suitable answers to inquiries made by users. To teach the machine learning model how to generate fitting responses, it will undergo training using an extensive collection of spoken interactions among humans for pattern recognition purposes. The Natural Language Processing (NLP) framework will serve as the foundation for the upcoming chatbot, which will utilize the Python programming language for its development. The model intends to apply advanced deep learning algorithms, including recurrent neural networks (RNN) as well as long short-term memory (LSTM), to analyze and interpret natural language and produce suitable replies. The model's accuracy will be enhanced by training it on a conversational log dataset, enabling it to learn from genuine interactions. Due to the swift advancement of technology and the emergence of the chatbot idea, the amount of time and effort can be conserved. A multitude of specialized frameworks have been developed to facilitate the creation and use of chatbots. The chatbot is dependent on artificial intelligence.