Software Engineering vs Machine Learning Concepts

Not all core concepts from software engineering translate into the machine learning universe. Here are some differences I've noticed. Divide and Conquer A key technique in software engineering is to break a problem down into simpler subproblems, solve those subproblems, and then compose them into a solution to the original problem. Arguably, this is the entire job, recursively applied until the solution can be expressed in a single line in whatever programming language is being used. The canonical pedagogical example is the Tower of Hanoi.