From aca94290972b80e539fa18b9c73158899a60b66b Mon Sep 17 00:00:00 2001
From: marina <138340846+bt3gl-cryptographer@users.noreply.github.com>
Date: Mon, 7 Aug 2023 16:51:23 -0700
Subject: [PATCH] Update README.md

---
 dynamic_programming/README.md | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/dynamic_programming/README.md b/dynamic_programming/README.md
index 3446e2b..b6bce42 100644
--- a/dynamic_programming/README.md
+++ b/dynamic_programming/README.md
@@ -50,11 +50,12 @@ def reverse(s):
 <br>
 
 * memoization is an optimization technique that avoids recursion's duplicate calculations.
-  
 * it's primarily used to speed up code by storing the intermediate results in a cache so that it can be reused later.
 * for example, a hash table can be used as a cache and should be passed along each subroutine call.
 * here is a basic template with pseudo-code:
 
+<br>
+
 ```python
 function dp(dp_state, memo_dict):
 
@@ -75,6 +76,8 @@ function answerToProblem(input)
 
 * classic examples where memoization can be used are fibonacci and the "climbing stairs" problem:
 
+<br>
+
 ```python
 cache = {1: 1, 0: 1}