Max Dot Product of Two Subsequences | Detailed | simplified | Leetcode 1458 | codestorywithMIK

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This is the 67th Video on our playlist "Dynamic Programming : Popular Interview Problems" by codestorywithMIK.
In this video we will try to solve a very Problem based on Recursion Memoization (DP) - Max Dot Product of Two Subsequences | Detailed | simplified | Leetcode 1458 | codestorywithMIK

Do let me know in the comment section if you would like to have a separate video on "Bottom Up" approach of this problem.

Trust me, this will no longer be a Hard Problem.
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.

Problem Name : Max Dot Product of Two Subsequences | Detailed | simplified | Leetcode 1458 | codestorywithMIK
Company Tags : AMAZON
My solutions on Github : https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/DP/Max%20Dot%20Product%20of%20Two%20Subsequences.cpp
Leetcode Link : https://leetcode.com/problems/max-dot-product-of-two-subsequences/

My DP Concepts Playlist : https://youtu.be/7eLMOE1jnls
My Graph Concepts Playlist : https://youtu.be/5JGiZnr6B5w
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My Recursion Concepts Playlist : https://www.youtube.com/watch?v=pfb1Zduesi8&list=PLpIkg8OmuX-IBcXsfITH5ql0Lqci1MYPM
Trie Playlist - https://www.youtube.com/watch?v=DMP2bqW6URA&list=PLpIkg8OmuX-I99uuP2BZOz4mI_lms4gVG
Difference Array Technique: Concepts & Qns : https://www.youtube.com/watch?v=ZHNVmtm08WY&list=PLpIkg8OmuX-Kqkb8DqDe_4-Tiav6ilS_L
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Video Summary :
We use DP on indices (i, j) to represent the maximum dot product we can form using subsequences starting from nums1[i] and nums2[j].
At each step, we either pair nums1[i] with nums2[j] or skip one element from either array, exploring all valid subsequences.
A large negative base case ensures we always pick at least one pair, even when all products are negative.
The DP chooses the best among taking the current pair alone, extending it, or skipping elements.
✨ Timelines✨
00:00 Introduction
00:39 Problem Explanation
02:46 Intuition + Thought Process + Tree Diagram
12:17 Story To Code
17:15 Time Complexity
18:29 Coding it up

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