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A practical and feature-rich paraphrasing framework to augment human intents in text form to build robust NLU models for conversational engines. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.
This chatbot project demonstrates the application of AI and ML techniques for natural language processing tasks. By training on a dataset of intents and responses, the chatbot is able to understand user queries and provide appropriate responses, making it a useful tool for various applications, including customer support, and more
Kowalski knows everything about Tennis and Kowalski is never wrong. Kowalski uses a Deep Neural Network Framework to train intent based dataset. It uses One-Hot Encoding and CBOW concepts to further improve the results.