Text-Based Chatbot Development | NLP Project (July 2023)

Designed and implemented a rule-based and intent-driven text chatbot capable of responding to user queries with contextual accuracy. Built using Natural Language Processing (NLP) techniques and deployed in a console-based environment for interactive communication.

Key contributions:

Created a structured intents JSON dataset with categories, patterns, and responses.

Utilized NLTK for tokenization, lemmatization, and preprocessing of user inputs.

Implemented the chatbot model using TensorFlow and scikit-learn, integrating a neural network classifier for intent prediction.

Developed a fallback response system for unknown queries to ensure smooth user interaction.

Focused on optimizing model accuracy and user engagement through continuous dataset improvement.

This project enhanced my practical knowledge in NLP, deep learning, and human-computer interaction, and laid the groundwork for future developments in AI-driven educational and support chatbots.