I thought the introduction (section 5.1) to this chapter was good. They provided a good general idea of what statistical machine learning is. I particularly thought that they covered the ideas of overfitting and underfitting well. I think the introduction could have been made a little bit better with a few more concrete examples (rather than just seeing the problem of learning some function).

Also, I found the more technical sections slightly less approachable. I think the authors could have done a better job of defining the vocabulary and terms and, again, added some more less technical examples and explanations (althought this is just my bias since I lean towards applications rather than pure theory :)