Dynamic Programming: Coin Change

Related lectures (23)

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Explores safe mutation in functional programming through lazy evaluation, object invariants, and efficient caching functions.

Explores the coin change problem, comparing greedy and dynamic programming algorithms for optimal solutions.

Explores dynamic programming through rod cutting and change making optimization problems.

Explores designing algorithms with recursion and dynamic programming, covering concepts like the Towers of Hanoi and efficient solutions.

Explores dynamic programming through binomial coefficients calculation, emphasizing efficiency and memoization in problem-solving.

Explores problem-solving strategies like recursion and divide and conquer methods, with examples such as the Towers of Hanoi.

Explains Optimal Binary Search Trees using dynamic programming and covers a midterm exam from 2016.

Explores dynamic programming for efficient problem-solving, illustrated with binomial coefficients and Pascal's triangle.

Explores the Tower of Hanoi algorithm, recursion, and dynamic programming in solving problems efficiently.

Covers dynamic programming with a focus on Fibonacci numbers and the rod cutting problem.