From fda87c1d4c115548f01ca502224295283ea11b73 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jan=20Sch=C3=A4r?= <jscissr@gmail.com>
Date: Wed, 31 Aug 2016 20:12:55 +0200
Subject: [PATCH] Fix typo

Bernoilli -> Bernoulli
---
 book/prob.tex | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/book/prob.tex b/book/prob.tex
index 13186ed..a3129ae 100644
--- a/book/prob.tex
+++ b/book/prob.tex
@@ -459,7 +459,7 @@ \section{Generative Stories}
 make things interesting, consider a multiclass classification problem,
 with continuous features modeled by independent Gaussians.  Since the
 label can take values $1 \dots K$, you can use a discrete
-distribution (die roll) to model it (as opposed to the Bernoilli
+distribution (die roll) to model it (as opposed to the Bernoulli
 distribution from before):
 %
 \begin{enumerate}