Fixed a typo in the markdown.

Author: jdwittenauer

DynamicProgramming.ipynb

@@ -243,7 +243,7 @@
    "source": [
     "The Fibonacci problem is a good starter example but doesn't really capture the challenge of representing problems in terms of optimal sub-problems because for Fibonacci numbers the answer is pretty obvious.  Let's move up one step in difficulty to a problem known as the [longest increasing subsequence](https://en.wikipedia.org/wiki/Longest_increasing_subsequence) problem.  The objective is to find the longest subsequence of a given sequence such that all elements in the subsequence are sorted in increasing order.  Note that the elements do not need to be contiguous; that is, they are not required to appear next to each other.  For example, in the sequence [ 10, 22, 9, 33, 21, 50, 41, 60, 80 ] the longest common subsequence (LIS) is [10, 22, 33, 50, 60, 80].\n",
     "\n",
-    "It turns out that it's fairly difficult to do a \"brute-force\" solution to this problem.  The dynamic programming solution is much more concise and a natural for the problem definition, so we'll skip creating an unnecessarily complicated naive solution and jump straight to the DP solution."
+    "It turns out that it's fairly difficult to do a \"brute-force\" solution to this problem.  The dynamic programming solution is much more concise and a natural fit for the problem definition, so we'll skip creating an unnecessarily complicated naive solution and jump straight to the DP solution."
    ]
   },
   {