Presentation was given at Data Science Festival (London, UK) and NCrafts (Paris, France), 2017

1. Using Machine Learning and Chatbots
to handle 1st line Technical Support
Barbara Fusinska
@BasiaFusinska

2. About me
Programmer
Machine Learning
Data Solutions Architect
@BasiaFusinska
https://github.com/BasiaFusinska/TechSupportChatBot

3. Agenda
• What is a chatbot?
• Why would you use it?
• How to build a chatbot?
• What are available tools?
• How to apply AI in a chatbot?

4. What’s a chatbot?

5. Turing Test:
Man vs the Machine

6. The Translator

7. The companion

8. Why would
you need a
machine on
the other
side?

9. Production
Chatbots
• Customer Service / Tech
Support
• FAQ
• Scripted scenarios
• Forms replacement
• Online ordering

10. Chatbot Architecture
Receive & Send
Messages
Process Message
System Integration

11. Chatbot
Platforms
Overview
• Microsoft’s Bot Platform
• Facebook’s Bots for Messenger
• Rebot.me
• Imperson
• ChatScript
• Pandorabots

12. UseCase:ITCrowd
AnsweringMachine

13. The IT Crowd Answering Machine
Demo

14. Scripted
solutions
• Conversation order
• Going off script
• Information retrieval
• Closed list of answers
• Regular expressions

15. Chatbots without machine learning

16. Natural
Language
Processing
• Information Extraction
• Guessing the context
(Intents)
• Retrieving data (Named
Entity Recognition)
• Creative Machines

17. Classification problem
Model training
Published model

18. Classification problem in NLP

19. Applying Artificial Intelligence
Receive & Send
Messages
Process Message
System Integration
AI

20. LUIS

21. Applying Intelligence to the Chatbot
Demo

22. Bot Framework
Challenges
• Training process
• Script vs Intents
• Classification errors
• Common phrases
• Hello/Goodbye
• Yes/No

24. Keep in touch
BarbaraFusinska.com
@BasiaFusinska
https://github.com/BasiaFusinska/TechSupportChatBot