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.
Who is This For ?
INTERMEDIATEPython Developers new to Chatbots
Click on each of the following annotated items to see details.
ARTICLE 1. An Introduction to Chatbot NLU
A short introduction on chatbots, NLU and NLU frameworks in the market.
PAPER 2. Recent Challenges in Task-Oriented Dialogue System
What are the state of the art model for chatbot NLU in academia?
ARTICLE 3. A short refresher on text classification
How do supervised text classification work (tokenization, train-test, evaluation)?
ARTICLE 4. Implementing Intent Classification with LSTM model
How do you implement Intent Classification?
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?
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?
ARTICLE 7. A short tutorial on how to use RASA NLU and RASA core
How to implement a simple POC chatbot with RASA?
WRITEUP 8. Other useful links
What if I want to learn more about Chatbots and RASA?