# All notes/ leet-code

## Logarithms

Let’s examine why algorithms such as binary search are described as O(log N).

## Time complexity of a recursive solution for Fibonacci Number without memoization

## Why merge_sort offer O(NlogN)?

## Performance: swap vs shift

## Why binary search offer O(log2N)?

## Understanding HASHING

## Why does binary search take O(logN)?

## Dynamic Programming vs Memoization

## Understand the QUEUE

## Understand the STACK