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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