In college, I was bored out of my mind during Linear Algebra, Multivariable Calculus, and Statistics courses. I wish the concepts would be introduced in the way they are in this book. For example, partial differentiation and gradients are explained in terms of neural network weight optimization / gradient descent. This book is especially valuable if you know the basic intuition behind machine learning and neural networks, and also have a basic intuition behind the math, and want to combine this intuition with a formal mathematical understanding.