In part 2 of our Guide to Big O Notation, we do a detailed walkthrough of the 7 common complexity Big O classes, explore how to analyze the complexity of functions with multiple inputs, and analyze the complexity of recursive functions.

In this video:
0:30 - Learning Objectives
1:00 - Constant: O(1)
5:49 - Logarithmic: O(log(n))
12:55 - Linear: O(n)
14:57 - Loglinear/ Linearithmic: O(n*log(n))
29:28 - Polynomial: O(n^c)
35:41 - Exponential: O(c^n)
42:00 - Factorial: O(n!)
44:57 - Complexity Hierarchy
47.09 - Analyzing Functions with Multiple Arguments
50:54 - Complexity for Recursive Functions
56:35 - Recap

Check out Part 1 of this Guide where we review the motivations behind Big O, how Big O works and the rules to implement Big O:    • The Complete Guide to Big O Notation ...  

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