Dynamic Programming
Dynamic Programming is a technique used in computer science and mathematics to solve complex problems by breaking them down into smaller subproblems and solving each subproblem only once. The solutions to the subproblems are stored in a table and used to solve larger problems. This technique is particularly useful when the same subproblems are encountered multiple times, as it avoids redundant calculations and improves efficiency. Dynamic Programming is commonly used in optimization problems, such as finding the shortest path in a graph or the maximum sum of a subarray. It is also used in machine learning algorithms, such as the Viterbi algorithm for hidden Markov models.
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