Regular Expression Matching | Brute Force | Optimal | Recursion Concepts And Questions

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This is the 18th video of our playlist "Recursion Concepts And Questions". Find the Details below :

Video Name : Regular Expression Matching | Brute Force | Optimal | Recursion Concepts And Questions
Video # : 18
C++/Java Code Link : https://github.com/MAZHARMIK/Intervie...
Leetcode Link : https://leetcode.com/problems/regular...

NOTE : We will also optimise the code by memoization (DP)

🔍 Unraveling Recursion: A Journey into the Depths of Code

🎥 Welcome to the 18th Video of my Recursion Playlist! 🚀 In this enlightening video, we will solve another very famous recursion problem "Regular Expression Matching". We will start with a Simple story as well as Tree Diagram for understanding the problem and then we will be Converting Story to code and writing the recursive code for the problem and I will also be explaining the Time and Space Complexity of the code 🌐.

🔍 What's Inside?

🔗 Simple story understanding with Tree Diagram

🔗 Converting Story to code and writing the recursive code for Regular Expression Matching problem

🔗 Explanation of Time and Space Complexity of the code

👩‍💻 Who Should Watch?

This playlist is for everyone but best suited for Freshers who are new to Recursion.

🚀 Embark on the Recursive Adventure Now!

My DP Concepts Playlist :    • Roadmap for DP | How to Start DP ? | ...  
My Graph Concepts Playlist :    • Graph Concepts & Qns - 1 : Graph will...  
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Approach Summary :
Approach-1 -
The solution uses recursion to check if a given text matches a pattern with wildcard characters '' and '.'. It handles base cases, matches the first character, and deals with '' by exploring two possibilities. The time complexity is exponential, and the space complexity is O(m), where m is the length of the pattern. While correct, this approach may benefit from optimization techniques for better efficiency.
Approach-2 -
In this approach, we will use i and j pointers in order to avoid substring call multiple times and we also memoize the code for optimal solution.

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✨ Timelines✨
00:00 - Introduction
04:08 - Though process from examples
25:13 - Tree Diagram
31:07 - Story To Code
38:42 - Time & Space Complexity
41:22 - Coding Story To Code
46:51 - Optimisation
48:39 - Coding Optimal Approach


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