This course aims to teach learners how to utilize the Mindmeld open-source platform to build advanced enterprise conversational assistants. By the end of the course, students will be able to develop voice and text-based AI assistants with deep-domain knowledge bases to handle complex use-cases. The course covers topics such as natural language processing, domain and intent classification, entity recognition, role labeling, language parsing, dialogue management, and entity resolution. The teaching method involves a combination of theoretical explanations and practical examples. This course is intended for developers and AI enthusiasts interested in creating sophisticated conversational AI applications for enterprise use.
Mindmeld - An Open-source, Deep-domain Conversational AI Toolkit
Overview
Syllabus
Intro
Conversational interfaces are the next frontier
Building production-quality conversational assistants is one of today's hardest Al challenges
Today's machine learning tools are insufficient Cloud NLP Services
The Mind Meld Conversational Al Platform
Github
Natural Language Processor understands the user query
Domain Classifier assigns the user query to a pre- defined domain
Intent Classifier determines the user intent
Entity Recognizer detects all relevant entities in the user query
Role Classifier assigns role labels to extracted entities
Entity Resolver transforms each extracted entity into its canonical form
Language Parser clusters extracted entities into meaningful entity groups
Dialogue Manager directs the flow of the conversation
Application Manager is the platform orchestrator
A sample interaction with an enterprise voice assistant
Domain Classification
Intent Classification
Entity Recognition
Role Classification
Language Parsing
Dialogue Management & Question Answering
Entity Resolution
Taught by
Linux Foundation
