I'm an undergraduate who took a course based on this book. While I agree that the book is not good at being a "foundations" book, I would say the ideas taught i

I'm an undergraduate who took a course based on this book. While I agree that the book is not good at being a "foundations" book, I would say the ideas taught in the book are very helpful in building an intuition for data science. For example: n real numbers independently taken from a standard normal distribution, normalized to be length 1, forms a random vector on a n-dimensional sphere. While these facts are not significant in the sense that I could apply them to a problem directly or use them to prove a theorem, these concepts appear frequently in data science problems and I know immediately that a graph is not a random graph by testing one of the properties of a random graph.