**1. Constant Complexity - O(1)**

The time taken will not grow no matter how much the input grows

**2. Logarithmic Time - O(LogN)**

The time taken will grow as the input grows but not as fast, for example a Binary Search

**3. Linear Time - O(n)**

As the problem grows, the time grows correspondingly with it, for example a Linear Search

**4. Polynomial Time - O(N^k)**

1/2 (N^2 - N) Half of N squared minus N

**5. Exponential Time - O(K^n)**

Only small problems can be solved in a reasonable amount of time

**6. Factorial Time O(N!)**

E.g Travelling salesman

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