ARTICLEAn Introduction to Chatbot NLU

Covers: theory of NLU for Chatbot using RASA
Questions this item adddesses:
  • A short introduction on chatbots, NLU and NLU frameworks in the market.
How to use this item?

Read until before the "Getting started with RASA" and optionally more.


Building your chatbot with Rasa-NLU

Zach NguyenTotal time needed: ~2 hours
Learning Objectives
The user of the short list will be able to understand the role of the Natural Language Understanding component of a task-oriented chatbot and build it for their own use case with conceptual knowledge and RASA hands-on guide.
Potential Use Cases
You are looking to build a chatbot for yourself or your company or are learning the fundamentals about how chatbots work.
Target Audience
INTERMEDIATEPython Developers new to Chatbots
Go through the following annotated items in order:
ARTICLE 1. An Introduction to Chatbot NLU
  • A short introduction on chatbots, NLU and NLU frameworks in the market.
10 minutes
PAPER 2. Recent Challenges in Task-Oriented Dialogue System
  • What are the state of the art model for chatbot NLU in academia?
10 minutes
ARTICLE 3. A short refresher on text classification
  • How do supervised text classification work (tokenization, train-test, evaluation)?
15 minutes
ARTICLE 4. Implementing Intent Classification with LSTM model
  • How do you implement Intent Classification?
15 minutes
ARTICLE 5. Implement Intent Classification with State of the Art BERT model
  • How do you implement Intent Classification with a State of the art Model?
20 minutes
ARTICLE 6. Implement Slot Filling with Recurrent Neural Network
  • How does Slot Filling work? What are the input and labels and how to train them using deep learning?
20 minutes
ARTICLE 7. A short tutorial on how to use RASA NLU and RASA core
  • How to implement a simple POC chatbot with RASA?
20 minutes
WRITEUP 8. Other useful links
  • What if I want to learn more about Chatbots and RASA?
20 minutes

Concepts Convered