Machine Learning for the Quantified Self by Mark Hoogendoorn & Burkhardt Funk

Author:Mark Hoogendoorn & Burkhardt Funk
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

6.2 Learning Theory

In the previous section we studied the learning process and its elements. The question we are concerned with in this section is: is it guaranteed that machines can learn as discussed above? The answer of Radio Yerevan would probably be: “In principle, yes, but ...”. To elaborate this answer, we present in this section the main ideas of the underlying theory without going into the mathematical details. Our goal is to provide a conceptual underpinning for choosing the right hypothesis set and evaluating the learning results. You might find it tricky to understand every step in this section, if you do not have some working knowledge in probability theory. In this case, try to follow the basic flow of arguments.

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