A graph can be defined as a group of vertices and edges that are used to connect these vertices. A graph can be seen as a cyclic tree, where the vertices (Nodes) maintain any complex relationship among them instead of having a parent-child relationship. A graph G can be defined as an ordered set G(V, E) where V(G) represents the set of vertices and E(G) represents the set of edges that are used to connect these vertices.

In this “Graph Algorithms – Data Structure and Algorithms” you will learn about the following topics:

1. Introduction of Graph
2. Graph Terminology
3. Graph Representation
5. Graph Algorithms
6. Terminologies in Graph Algorithms
7. Types of Graph Algorithms
9. Implementation of Breadth First Search (BFS)
10. Depth First Search (DFS) Algorithm
11. Implementation of Depth First Search (DFS)
12. Topological Sort
13. Spanning Tree
14. General Properties of Spanning Tree, Mathematical Properties of Spanning Tree
15. Minimum Spanning Tree (MST)
16. Kruskal's Algorithm, Prim's Algorithm
17. Dijkstra's Algorithm
18. How Dijkstra's Algorithm Works?
19. Example of Dijkstra's Algorithm
20. Implementation of Dijkstra’s Algorithm
21. Network Flow Problems
22. Residual Networks, Augmenting Path

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