🚀 Graph Tutorial 8: Number of Islands | Count Connected Components in Matrix | Data Structures

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►► Problem: Given an m x n 2D binary grid grid which represents a map of '1's (land) and '0's (water), return the number of islands. An island is surrounded by water and is formed by connecting adjacent lands horizontally or vertically. You may assume all four edges of the grid are all surrounded by water.
► Input: grid = [
["1","1","1","1","0"],
["1","1","0","1","0"],
["1","1","0","0","0"],
["0","0","0","0","0"]
] Output: 1

Welcome to my detailed walkthrough of the popular LeetCode problem "Number of Islands"! In this video, I’ll show you how to solve this grid-based problem using Breadth-First Search (BFS) and Depth-First Search (DFS) graph traversal techniques. This problem is commonly asked in coding interviews, so mastering its solution is essential for success.

Here’s what you’ll learn in this video:
🔹 Problem Statement – A clear understanding of the "Number of Islands" problem.
🔹 Approach – How to think about grid traversal as a graph problem.
🔹 BFS Solution – How to implement BFS to find connected components in a grid.
🔹 DFS Solution – How to apply DFS recursively to solve the same problem.
🔹 Java Code Explanation – A complete, line-by-line code walkthrough in Java, covering all edge cases.
🔹 Time & Space Complexity Analysis – Understand the efficiency of both approaches.

By the end of this video, you'll have a solid understanding of BFS and DFS graph traversal in the context of grid problems, which will help you tackle similar interview questions with confidence.

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