Building your own conversational AI with open source tools
Point-and-click tools like Dialogflow and LUIS are great for building simple prototypes of conversational agents. But they don’t scale well beyond answering simple questions. In this live-coding talk, you will learn the fundamentals of conversational AI and how to build your own that can handle more complex back-and-forth conversations using open source libraries.
Tags: Artificial Intelligence, NLP, Machine Learning, Python
Scheduled on friday 10:30 in room media
Justina has a background in Econometrics and Data Analytics. Her curiosity for Data Science and human behaviour analytics has taken her to many places and industries – over the past three years she has been doing Data Science work across video gaming, fintech, insurance industries. Her interest in chatbots, natural language processing and open source has led her to Rasa, a Berlin-based conversational AI startup where she works as a Developer Advocate focusing on improving developer experience in using open source software for conversational AI.
Conversational AI is far from being a solved problem, but you don’t need to rely on third-party APIs to build great chat and voice apps.
In this talk we will live-code a useful, engaging conversational AI bot based entirely on machine learning. We’ll be using Rasa NLU & Rasa Core, which are open source libraries for building machine learning-based chatbots and voice assistants. We will teach our system how to hold multi-turn conversations by creating some initial training data, and then refine its behaviour by interacting with the system and providing feedback. We will cover the fundamentals of conversational AI, including the most important algorithms for intent classification, entity extraction, and dialogue management.
What will attendees learn:
- fundamentals of natural language understanding and dialogue management for building intelligent assistants.
- deep dive into the open source libraries Rasa NLU and Rasa Core.
- open challenges.