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+# Time Complexity
+
+## Big O
+
+Big O is a way to categorize an algorithm's time or memory requirements based on
+input. It is not meant to be an exact measurement. It will not tell you how many
+CPU cycles it takes, instead it is meant to generalize the growth of the
+algorithm as the input grows.
+
+- Look for loops
+- Constants are dropped (Big O describes the upper bound or growth of the
+  algorithm where the constant eventually becomes irrelevant)
+- We often only consider worst case (e.g., searching through a list where the
+  element you want is the last one)