Topic 11c
Types of Learning

Learning Outcomes

By the end of this topic students should be able to:

  • Provide a definition for [imitation| supervised learning | unsupervised learning | reinforcement learning].
  • Discuss a specific example of where a human is learning through [imitation | supervised learning | unsupervised learning | reinforcement learning].
  • Discuss one example of machine learning and explain whether it is supervised learning, unsupervised learning, or reinforcement learning.

 

Learning Materials

  • Readings
    • The three types of learning - pp 589-591
      • The book mentions imitation which we will not consider a form of learning in this course.
  • Videos
    • Crash Course AI #2 - Supervised Learning
      • Note, the most important part of this video is in the introduction of this video.
        • Watch from 0-2:46
      • The second half of the video goes pretty deeply into Artificial Neural Networks (aka ANNs) - which is Topic 11.5. I suggest you watch it but don't worry about the ANN details. Focus only on the information dealing with the supervised learning that takes place with a neural network.
    • Crash Course AI #6 - Unsupervised Learning
      • Again, a small part of this contains some discussion about ANNs. Don't worry about the details now. Instead, focus on what is happening with unsupervised learning.
    • Crash Course AI #9 - Reinforcement Learning

     

Checking for Understanding

This particular section doesn't have cut-and-dry questions and answers from the book.

  • Could you define each of the four learning techniques?
  • Could you give an example of each of the four learning techniques?

 

Additional Guidance

  • NA

Further Information

  • NA