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Put AI to work
8-9 Oct 2018: Training
9-11 Oct 2018: Tutorials & Conference
London, UK

Deprecating the state machine: Building conversational AI with the Rasa stack

Alan Nichol (Rasa)
16:50–17:30 Wednesday, 10 October 2018
Implementing AI
Location: Windsor Suite
Secondary topics:  Platforms and infrastructure, Retail and e-commerce, Text, Language, and Speech
Average rating: ****.
(4.50, 2 ratings)

Who is this presentation for?

  • Developers, engineers, data scientists, and technical executives

Prerequisite knowledge

  • Familiarity with Python and basic ML concepts like training data and supervised learning

What you'll learn

  • Explore the Rasa NLU and Rasa Core open source libraries
  • Understand the fundamentals of natural language understanding and dialogue management for building intelligent assistants, along with widely used algorithms
  • Learn best practices for managing training data


There’s a large body of research on machine learning-based dialogue, but most voice and chat systems in production are still implemented using a state machine and a set of rules. Rasa NLU and Rasa Core are the leading open source libraries for building machine learning-based chatbots and voice assistants.

Alan Nichol walks you through building fully machine learning-based voice and chatbots with the open source Rasa stack. You’ll start with language understanding, bootstrapping from very little annotated training data, before building up your bot’s ability to handle increasingly complex dialogues through supervised and interactive learning.

Photo of Alan Nichol

Alan Nichol


Alan Nichol is cofounder and CTO of leading open source conversational AI company Rasa, where he helps create the software that enables developers to build conversational software that really works. Rasa is trusted by thousands of developers in enterprises worldwide, including UBS, ERGO, and Helvetia. Alan has years of experience building AI-powered products in industry and is the author of the DataCamp course Building chatbots in Python. He was featured in Forbes’s 30 under 30 list. Alan holds a PhD in machine learning from the University of Cambridge.