Reading Questions for Lecture 1
Introduction / Machine Learning (Ch. 1)
- Classification: What is a discriminant?
- Regression: to train an autonomous car to predict what angle to turn the steering wheel, where could the training data come from?
Supervised Learning (Ch. 2.1, 2.4-2.9)
- Is the most specific hypothesis S a member of the version space? Why or why not?
- What happens if the true concept C is not in the version space?
- What is Occam's Razor?
- (Grady) What is a version space?
- (Grady) How do you get Empirical Error?
- (Jillian) With regards to hypotheses classes, what defines a case of doubt and why do we have doubt?<