11 Supervised and unsupervised learning

 

This chapter covers

  • Reviewing the basics of artificial intelligence, machine learning, and deep learning
  • Understanding graph machine learning, graph embedding, and graph convolutional networks
  • Understanding attention mechanisms
  • Understanding self-organizing maps
  • Solving optimization problems using supervised and unsupervised machine learning

11.1 A day in the life of AI-empowered daily routines

11.2 Demystifying machine learning

11.3 Machine learning with graphs

11.3.1 Graph embedding

11.3.2 Attention mechanisms

11.3.3 Pointer networks

11.4 Self-organizing maps

11.5 Machine learning for optimization problems

11.6 Solving function optimization using supervised machine learning

11.7 Solving TSP using supervised graph machine learning

11.8 Solving TSP using unsupervised machine learning

11.9 Finding a convex hull

Summary