Big O Notation

Big O notation is a way to characterize the time or resources needed to solve a computing problem, including those encountered in Machine Learning and AI.  It's particularly useful in comparing various computing algorithms under consideration. Below is a table summarizing Big O functions. The four most commonly referenced and important to remember are:

• O(1)              Constant access time such as the use of a hash table.
• O(log n)        Logarithmic access time such as a binary search of a sorted table.
• O(n)              Linear access time such as the search of an unsorted list.
• O(n log(n))   Multiple of log(n) access time such as using Quicksort or Mergesort.