Use machine learning to build bot (a) Introduction

Remember taught you to do object detection, taught you how to do NER series of article? Full of dry goods there are no O (∩_∩) O, most readers follow the steps to finally have achieved in which the object detection and named entity recognition project.

• Object detection
  
  
• Named entity recognition
  

This series of articles is still adhering to the practice-based theory supplemented, so that we "make out, to see to understand" principle, to showcase the features introduced, various aspects of design ideas, code implementation (python), such as the principle of the algorithm contents are involved, through the study of this series of articles, you will be able to achieve their own a bot.

table of Contents

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• The concept papers
  • What is a bot?
  • What are the common routine bot there?
• Design articles
  • Our chat robot will have what characteristics?
  • Open source chatbot framework ChatterBot Profile
  • ChatterBot enough?
  • What a problem given the experience from the input to reply?
  • How to make a robot that I want to hear?
• Code articles
  • Part module code
    • Feature vector configuration
      • one-hot way
      • Dristributed Representation way
    • Category intent
    • Semantic Matching
    • chatterbot training
    • e-learning
• Access articles
  • Access step
  • Interface Description
• Principle articles
  • word2vec
  • Cosine similarity
  • Naive Bayes
  • Naive Bayes polynomial
  • Levenshtein distance
• Summary article

The next article, "taught you how to build a bot (a) the concept papers" chat robot will make a presentation of the concepts.

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