Perfect Squares | Bottom UP | Made Easy | Google | Leetcode 279
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This is the 86th Video of our Playlist "Dynamic Programming : Popular Interview Problems".
In this video we will try to solve a very good DP problem - Perfect Squares | Leetcode 279
We will solve it using Bottom Up because we have already solved this using Recursion + Memo in another video (Link below) :
https://www.youtube.com/watch?v=Zbn8in7hpXY
We will be using the same Recursion + Memo code to convert it to 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 : Perfect Squares | Leetcode 279
Company Tags : Google, Salesforce, Microsoft, Meta, Amazon
My solutions on Github(C++ & JAVA) : https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/DP/Perfect%20Squares.cpp
Leetcode Link : https://leetcode.com/problems/perfect-squares/description/
My Recursion Concepts Playlist : https://www.youtube.com/watch?v=pfb1Zduesi8&list=PLpIkg8OmuX-IBcXsfITH5ql0Lqci1MYPM
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 approach utilizes dynamic programming and an array t to store the minimum number of perfect squares required for each number from 0 to n. The algorithm iterates through each number, decomposing it into the sum of a perfect square and a remaining number. It calculates the minimum number of perfect squares needed for the current number based on the subproblem solutions. The final result is the minimum number of perfect squares required to sum up to the input n.
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✨ Timelines✨
00:00 - Introduction
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