From e95e20d68198f0d86108ba6db30576d70741fbd5 Mon Sep 17 00:00:00 2001
From: Vijay Janapa Reddi <vj@eecs.harvard.edu>
Date: Mon, 30 Oct 2023 12:29:41 -0400
Subject: [PATCH] Note fix

---
 benchmarking.qmd | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/benchmarking.qmd b/benchmarking.qmd
index 85e3121f9..0adc1acc6 100644
--- a/benchmarking.qmd
+++ b/benchmarking.qmd
@@ -7,7 +7,7 @@ Benchmarking is a critical part of developing and deploying machine learning sys
 This chapter will provide an overview of popular ML benchmarks, best practices for benchmarking, and how to use benchmarks to improve model development and system performance. It aims to provide developers with the right tools and knowledge to effectively benchmark and optimize their systems, especially for tinyML systems.
 
 ::: {.callout-tip collapse="true"} 
-Learning Objectives
+## Learning Objectives
 
 * Understand the purpose and goals of benchmarking AI systems, including performance assessment, resource evaluation, validation, and more.