Implementing a Flask-based Chatbot for College Enquiries using Spacy and TensorFlow

This research paper presents the development of a chatbot for natural language processing (NLP) using
Spacy and TensorFlow libraries in a Flask-based application. The chatbot is trained using a deep
learning model and is capable of responding to user inquiries in a conversational manner. The paper
describes the process of data preprocessing, tokenization, and feature extraction, which are used to train
the model. The chatbot's performance is evaluated using various metrics such as accuracy and F1 score,
and the results are compared with other existing chatbot models. The paper concludes that the Spacy and
TensorFlow-based chatbot provides a reliable and efficient solution for NLP tasks and can be further
improved by incorporating more advanced NLP techniques. The chatbot's ease of integration with other
systems and platforms, as well as its ability to learn and adapt to new input data, makes it a valuable tool
for a wide range of applications.