Dynamic Programming (DP) is a technique used in computer science and mathematics to solve problems by breaking them down into smaller overlapping subproblems. It stores the solutions to these subproblems in a table or cache, avoiding redundant computations and significantly improving the efficiency of algorithms. Dynamic Programming follows the principle of optimality and is particularly useful for optimization problems where the goal is to find the best or optimal solution among a set of feasible solutions.
You may ask, I have been relying on recursion for such scenarios. What’s different about Dynamic Programming?