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• Introduction to ChatBots
• Overview of Conversational Software
• Building Your First Basic ChatBot
• Setting Up Your ChatBot to Receive Text and Respond to Users
  Adding the Basic Elements of Personality
  Teaching Your ChatBot to Answer Basic Questions
  Adding Variety to Your ChatBot's Responses
  Making Your ChatBot Ask Questions
  Building Rule-Based Systems for Parsing Text
  Using Machine Learning to Turn Natural Language into Structured Data for Your ChatBot
• Overview of SpaCy, Scikit-learn, and Rasa NLU
  Installing and Configuring SpaCy, Scikit-learn, and Rasa NLU
  Intents and Entities and their Classifications
  Natural Language Processing Fundamentals Theory Refresher
  Building Models from Real-World Sentences Using the ATIS Dataset
  Building Your Virtual Assistant ChatBot
• Overview of a Virtual Assistant
  Working with SQL in Python
  Teaching Your ChatBot to Access Data from a Database
  Writing Queries from Parameters
  Building a Database from Natural Language
  Implementing Custom Virtual Assistant Features on Your ChatBot
  Answering Specific Queries through Database Access
  Refining Search, Performing Basic Negation, and Filtering Data
  Making Your ChatBot Stateful: Keeping Track of States of Interaction for Better ChatBot Dialogs
• Performing Basic Actions
  Asking Contextual Questions and Queuing Answers
  Dealing with Rejection
  Testing and Deploying Your ChatBot
• Troubleshooting
• Summary and Conclusion