Applications of Graph
Following are the real-life applications:
- Graph data structures can be used to represent the interactions between players on a team, such as passes, shots, and tackles. Analyzing these interactions can provide insights into team dynamics and areas for improvement.
- Commonly used to represent social networks, such as networks of friends on social media.
- Graphs can be used to represent the topology of computer networks, such as the connections between routers and switches.
- Graphs are used to represent the connections between different places in a transportation network, such as roads and airports.
- Graphs are used in Neural Networks where vertices represent neurons and edges represent the synapses between them. Neural networks are used to understand how our brain works and how connections change when we learn. The human brain has about 10^11 neurons and close to 10^15 synapses.
Graph Data Structure And Algorithms
Graph Data Structure is a collection of nodes connected by edges. It’s used to represent relationships between different entities. Graph algorithms are methods used to manipulate and analyze graphs, solving various problems like finding the shortest path or detecting cycles.
Table of Content
- What is Graph Data Structure?
- Components of a Graph
- Basic Operations on Graphs
- Applications of Graph
- Basics of Graph
- BFS and DFS in Graph
- Cycles in Graph
- Shortest Path in Graph
- Minimum Spanning Tree
- Topological Sorting
- Connectivity in Graph
- Maximum Flow in Graph
- Some must do Problems on Graph
- Some Quizzes
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