String Compression II | Recursion | Memo | Leetcode 1531

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Published on ● Video Link: https://www.youtube.com/watch?v=6rgO0obJG0k


Duration: 41:52
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This is the 77th Video of our Playlist "Dynamic Programming : Popular Interview Problems".
In this video we will try to solve a very good DP problem - String Compression II (Leetcode 1531).
We will solve it using Recursion Memoization in this video and I will post a separate video by Bottom Up.

I will explain the intuition so easily that you will never forget and start seeing this as cakewalk EASYYY.
We will do live coding after explanation and see if we are able to pass all the test cases.
Also, please note that my Github solution link below contains both C++ as well as JAVA code.

Problem Name : String Compression II
Company Tags : will update soon
My solutions on Github(C++ & JAVA) : https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/strings/String%20Compression%20II.cpp
Leetcode Link : https://leetcode.com/problems/string-compression-ii/

My DP Concepts Playlist : https://youtu.be/7eLMOE1jnls
My Graph Concepts Playlist : https://youtu.be/5JGiZnr6B5w
My GitHub Repo for interview preparation : https://github.com/MAZHARMIK/Interview_DS_Algo
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Approach Summary : The code uses dynamic programming with a 4D memoization table to find the optimal compression length of a given string 's' by deleting at most 'k' characters. The recursive function explores options for deleting or keeping characters based on specific conditions. The approach aims to minimize the compressed string length, and a global heap-allocated memoization table avoids stack overflow. The 'getLengthOfOptimalCompression' function initializes the table and calls the recursive solver.

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✨ Timelines✨
00:00 - Introduction

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