This is more of a note-taking space right now. I’m following along

coding-interview-university

laneparton • Updated Sep 7, 2022

**Algorithmic complexity / Big-O / Asymptotic analysis**

- Nothing to implement here, you're just watching videos and taking notes! Yay!

- There are a lot of videos here. Just watch enough until you understand it. You can always come back and review.

- Don't worry if you don't understand all the math behind it.

- You just need to understand how to express the complexity of an algorithm in terms of Big-O.

## Harvard CS50 - Asymptotic Notation (video)

- O(n) = linear complexity

- O(1) = constant complexity

- O(log n) = logarithmic complexity

- Ω = Best case constant

- Θ = best and worst case scenarios are the same

- Binary Search -
- Starts in the middle
- If > checks left
- If > checks right
- Repeat…

## Big O Notations (general quick tutorial) (video)

- Measure how well a computer algo scales as the amount of data increases
- 10 element array vs 10,000 element array

TopCoder (includes recurrence relations and master theorem):