LeetCode 150 Roadmap - Dynamic Programming Part 2 (Coin Change, Word Break, Partitions)

Dynamic programming is a method for efficiently solving complex problems by breaking them down into simpler subproblems, solving each of these subproblems just once, and storing their solutions. The key idea is to avoid the computation of the same subproblem multiple times, which is a common issue in naive recursive approaches that leads to exponential time complexity for many problems.

Dynamic programming can be applied when the problem has a recursive structure that includes overlapping subproblems and can be characterized by a set of optimal substructure properties—meaning the solution to the problem can be constructed from the solutions to its subproblems.

Questions covered in this video:

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