Reading the bound

In the book: Chapter 1, §"Why the Perceptron Works" (closing); foreshadows Chapter 2. Builds on: The convergence theorem.

Planned. Interprets the mistake bound $(R/\gamma {)}^2$: the number of updates does not depend on the number of examples or the dimension, only on the geometry — how spread out the data is ($R$) versus how wide the best separating corridor is ($\gamma$). Discusses what happens when the data is not separable, and why the appearance of the margin $\gamma$ in the bound is the mathematical seed of Chapter 2's search for the sharpest line.