The Conversational AI Playbook
4.5.0

Introduction

  • Introduction to Conversational Applications
  • Different Approaches for Building Conversational Applications
  • Anatomy of a Conversational AI Interaction
  • Introducing MindMeld
  • Key Concepts

Step-by-Step Guide

  • Building a Conversational Interface in 10 Steps
  • Step 1: Select the Right Use Case
  • Step 2: Script Your Ideal Dialogue Interactions
  • Step 3: Define the Domain, Intent, Entity, and Role Hierarchy
  • Step 4: Define the Dialogue State Handlers
  • Step 5: Create the Knowledge Base
  • Step 6: Generate Representative Training Data
  • Step 7: Train the Natural Language Processing Classifiers
  • Step 8: Configure the Language Parser
  • Step 9: Optimize Question Answering Performance
  • Step 10: Deploy Trained Models

Blueprint Applications

  • MindMeld Blueprints
  • Food Ordering
  • Video Discovery
  • Home Assistant
  • HR Assistant
  • Banking Assistant
  • Health Screening

User Guide

  • Getting Started
  • Platform Architecture
  • Managing Optional Dependencies
  • Working with the Natural Language Processor
  • Working with the Domain Classifier
  • Working with the Intent Classifier
  • Working with the Entity Recognizer
  • Working with the Role Classifier
  • Working with the Entity Resolver
  • Working with the Language Parser
  • Working with User-Defined Features
  • Working with the Knowledge Base and Question Answerer
  • Working with the Dialogue Manager
  • Working with the Text Preparation Pipeline
  • Working with the Auto Annotator
  • Working with Custom Actions
  • Active Learning in MindMeld
  • Data Augmentation in MindMeld
  • Deep Neural Networks in MindMeld
  • Internationalization support
  • Dealing with Voice Inputs
  • DVC & DAGsHub for Model Tracking
  • Webex Teams Integration
  • WhatsApp Integration

Walk-Throughs

  • Step-by-Step Guide to Active Learning with Log Data in MindMeld

API

  • API Reference

MindMeld UI

  • MindMeld UI

Versions

  • Recent Changes
  • Package History
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