"Software", like "science", is a broad term. Just like there are many kinds of scientists and you could be, say, a biologist or a physicist, there are many entirely disparate fields of software engineering. At the end of the day, software itself is just a means to an ends: solving a problem. Solving some of these problems like the one that GP discussed have more to do with math than programming. The programming is mostly the implementation of the math. So if you're not versed in that math, of course you wouldn't understand the code that's being written to implement it.
Building machine learning systems is vastly different from building operating systems which is vastly different from embedded systems which is vastly different from networking which is vastly different what most of us do (myself included), which is building CRUD apps. We're just solving different problems. Of course there are common themes to writing good code, just like there are common themes to performing science, but the code and solutions will look almost nothing alike.
Building machine learning systems is vastly different from building operating systems which is vastly different from embedded systems which is vastly different from networking which is vastly different what most of us do (myself included), which is building CRUD apps. We're just solving different problems. Of course there are common themes to writing good code, just like there are common themes to performing science, but the code and solutions will look almost nothing alike.