Lec 3 | Graph Representation ( Adjacency Matrix ) | Data Structures | BTech 2nd Year

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This lecture explains Graph Representation using Adjacency Matrix, one of the most important and frequently asked topics in Data Structures university exams.

Adjacency matrix representation is commonly used to store graphs in memory and is the foundation for many graph algorithms.

✅ You Will Learn (Exam-Oriented):

What is Graph Representation
Meaning of Adjacency Matrix
How to construct adjacency matrix step-by-step
Adjacency matrix for undirected graph
Adjacency matrix for directed graph
Adjacency matrix for weighted graph
Memory representation of adjacency matrix
Time & space complexity
Advantages and disadvantages
How adjacency matrix questions are asked in exams

The explanation is diagram-based, step-wise, and strictly exam-focused, ideal for 5–10 mark questions and viva.

📘 This Data Structures Playlist Covers:

Graph introduction & terminologies
Graph representation (Adjacency Matrix & List)
Graph traversal (BFS & DFS)
Shortest path algorithms
Minimum spanning trees

🎯 This Video Is Helpful For:

BTech 2nd Year students
Data Structures exam preparation
Understanding graph storage in memory
University exam & viva preparation
GATE & competitive exam basics

🏷️ Keywords :

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