Graph Coloring for Data Science: A Comprehensive Guide

Graph coloring is a combinatorial problem of assigning labels to graph nodes such that no two adjacent nodes share the same color. The concept is introduced through a puzzle involving coloring flower petals, which is modeled as a cyclical graph. A recurrence relation is derived to solve the problem, followed by the derivation of a more efficient closed-form analytical solution. The article also provides a Python function to compute the number of proper colorings and discusses practical data science applications like scheduling, timetabling, and resource allocation using conflict graphs.