It is easy to make a fast, incorrect algorithm. In machine learning, we are often faced with two challenges: correctly implement a complicated, math-heavy algorithm and make it run fast! In this talk, we present the marrying of functional programming and machine learning as a solution to this central problem dogging machine learning practitioners. As a demonstration of combining these ideas together, we present code that implements common learning algorithms using core principles of functional programming.
