Dynamic programming is a technique for solving problems, whose solution can be expressed recursively in terms of solutions of overlapping sub-problems. A gentle introduction to this can be found in How Does DP Work? Dynamic Programming Tutorial.

Memoization is an optimization process. In simple terms, we store the intermediate results of the solutions of sub-problems, allowing us to speed up the computation of the overall solution. The improvement can be reduced to an exponential time solution to a polynomial time solution, with an overhead of using additional memory for storing intermediate results.

Let's understand how dynamic programming works with memoization with a simple example.