Longest Common Subsequence Using Dynamic Programming || GATECSE || DAA

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Dive into a detailed tutorial on solving the Longest Common Subsequence (LCS) problem using Dynamic Programming (DP)! This video is designed to enrich your understanding of both the LCS problem and the dynamic programming approach to solving complex computational issues efficiently.

⚙️ What You’ll Learn:

Introduction to LCS: Explore what the Longest Common Subsequence is and its significance in the world of computer science.
Dynamic Programming Explained: A primer on dynamic programming, a strategic method for solving complex recursive problems.
Applying DP to LCS: How to effectively use DP to unravel the LCS problem.
Code Walkthrough: Step-by-step coding session showing the implementation of LCS using dynamic programming.
Complexity Analysis: Discussion of the time and space complexity associated with the LCS solution.
Real-World Applications: Discover how LCS is used in various industries, including bioinformatics, text editor utilities, and data comparison.

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