Number of Unique Good Subsequences


10 Prerequisite LeetCode Problems
To tackle this, you should have a good understanding of dynamic programming (DP), binary numbers, and dealing with subsequences. Here are 10 problems to prepare:
300. Longest Increasing Subsequence: An essential problem to understand the basic idea of dealing with subsequences using dynamic programming.
673. Number of Longest Increasing Subsequence: An extension of the previous problem which also counts the number of longest increasing subsequences.
1143. Longest Common Subsequence: A classical problem in dynamic programming to understand how to compute the longest common subsequence.
1048. Longest String Chain: This problem requires a combination of string manipulation and dynamic programming.
516. Longest Palindromic Subsequence: An extension of the longest common subsequence problem, but within a single string.
931. Minimum Falling Path Sum: A problem to understand how dynamic programming can be used to find minimum paths.
646. Maximum Length of Pair Chain: This problem is about finding the longest chain of pairs, a concept that can be useful for subsequences.
918. Maximum Sum Circular Subarray: A twist on the classic maximum subarray problem where the subarray can be circular.
91. Decode Ways: This is a DP problem where you count the number of ways to decode a string.
509. Fibonacci Number: A simple DP problem to understand the basic concept of dynamic programming.
Working on these problems will give you a solid foundation in dynamic programming and subsequences, which are necessary for solving “1987. Number of Unique Good Subsequences”.