"With all due respect, what are 99 percent of people gaining from a book on, say, convex optimization? Yes, these are great choices if you're looking to become

"With all due respect, what are 99 percent of people gaining from a book on, say, convex optimization? Yes, these are great choices if you're looking to become an expert on, say, physics. But not everyone is a physicist, nor does everyone need to be." Convex Optimization for physicists??? Whaaaat? OK, consider Game Theory, Machine Learning, Operations Research. All have practical value and all require optimization. In fact, Machine Learning is mostly applied optimization theory. The Simplex algorithm is used all the time, in the most various industries. Yet once again, the need to know a bit of optimization theory is made evident. Physicists don't really require the kind of optimization on Boyd's book. Unless one is an experimental physicist and needs to analyze data sets. Theoretical physicists usually work with infinite-dimensional optimization, i.e., variational analysis. I entirely agree that not everyone is a physicist, nor does everyone need to be... but picking Convex Optimization as an example was a poor choice. The list is my personal list. It's a personal thing, and as such, it is non-transmissible. I am not trying to preach. I couldn't care less if the masses read junk...