Longest Common Subsequence | Dynamic Programming

In this video, I will explain how to do the Longest Common Subsequence as a dynamic programming problem. This problem appears in a lot of interviews. The longest common subsequence problem is the problem of finding the longest subsequence common to all sequences in a set of sequences. It differs from the longest common substring problem: unlike substrings, subsequences are not required to occupy consecutive positions within the original sequences. On the other hand, dynamic programming is both a mathematical optimization method and a computer programming method. The method was developed by Richard Bellman in the 1950s and has found applications in numerous fields, from aerospace engineering to economics. In both contexts it refers to simplifying a complicated problem by breaking it down into simpler sub-problems in a recursive manner. While some decision problems cannot be taken apart this way, decisions that span several points in time do often break apart recursively. Likewise, in computer science, if a problem can be solved optimally by breaking it into sub-problems and then recursively finding the optimal solutions to the sub-problems, then it is said to have optimal substructure.

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Thanks for making my life easier prof 🙏