This section contains some of the algorithms which are used to find shortest paths in a Graph.

## Shortest Path Algorithm in Unweighted Graph Using BFS

The shortest path between two vertices (or nodes) in a graph is the path that has the minimum number of edges or the minimum total weight (if the graph is weighted) between the two vertices. In other words, it is the path that requires the least amount of effort or cost to travel from one vertex to the other.
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## Dijkstra's Shortest Path Algorithm

Dijkstra’s shortest path algorithm is used to efficiently determine the shortest path between a starting node and an ending node in a graph, where each edge has a non-negative weight or cost associated with it. This algorithm is particularly useful in scenarios where you need to find the most efficient or cost-effective route, such as in transportation networks, communication networks, or any other systems that can be represented as a weighted graph.
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## Bellman-Ford Shortest Path Algorithm

The Bellman-Ford algorithm is a type of dynamic programming algorithm used to find the shortest paths from a single source vertex to all other vertices in a weighted graph. This algorithm is particularly useful when dealing with graphs that might contain negative-weight edges, which can cause issues for other shortest path algorithms like Dijkstra’s algorithm.
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