Data Science for Science

Courtesy: University of Tennessee Knoxville Hey Folks, We have an intriguing application of Machine Learning (ML) today: Knots and Symmetries in Mathematics! ML, as you're probably aware, works when we have a whole lot of data. In fact, the more data we have, the more likely we are to use ML or its more sophisticated brethren Deep Learning (DL). So without further ado, let's dive in! What are knots and symmetries in mathematics? A knot in mathematics is, as you would expect, inspired from real-life knots but isn't so exactly. Simply put a knot is a 2-D closed loop that exists in 3-D space. This concept could of course be extended to n-dimensional loops in m-dimensional space. Knots can be described mathematically in various ways. Sometimes two seemingly different descriptions are actually of the same knot. This can be determined by comparing properties of knots known as invariants . One of the questions surrounding invariants is: Are two invariants related? To answer this