REC 01:24:05
24 Students
Algorithm Complexity (Big O)
1. O(1) - Constant Time
2. O(log n) - Logarithmic Time (Binary Search)
3. O(n) - Linear Time (Simple loop)
for (let i = 0; i < n; i++) {
console.log(i);
}
4. O(n^2) - Quadratic Time (Nested loops)
Instructor (You)
Alex
Jordan
Sam
Taylor
Morgan
Class Chat Live
Alex 10:14 AM
Can you explain O(n^2) again?
Sam 10:15 AM
I think it means inside a loop there is another loop.
