No, I'm saying Hefferon is not applicable to any field. He eschews application in favor of formal theorem proving in vector spaces, in isolation of any real-life examples. That is great, but that is not the typical use case of anybody out there who actually uses linear algebra in industry, whether in computer graphics or portfolio theory or multivariate statistics or what have you.
Long before reading the book, I spent a lot of time with financial modeling of all kinds, but your complaint doesn't resonate with me at all. I went on to study machine learning and found the ideas in Hefferon laid a good foundation. It might be fair to point out that is not a cookbook and you don't use it to learn how to wrangle LAPACK, but I think it's over the top to say what you just did.
If you're looking to do application, use an applied book. Gilbert Strang's "Linear Algebra and its Applications" is quite good.