(K)not machine learning

We review recent efforts to machine learn relations between knot invariants. Because these knot invariants have meaning in physics, we explore aspects of Chern-Simons theory and higher dimensional gauge theories. The goal of this work is to translate numerical experiments with Big Data to new analytic results.
Comment: 10 pages, 2 figures, LaTeX, based on a talk given by VJ at the Nankai Symposium on Mathematical Dialogues, August 2021