Introduction To Graphs

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Practice Quiz →

Figure:

A graph represents relationships using nodes and edges. Nodes are the objects, and edges describe how they connect. Graphs can be directed or undirected, weighted or unweighted, and are used to model networks, maps, and systems.

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Related Topic(s):

🔥 Adjacency Matrix → Requires prior knowledge of vertices/edges, directed vs. undirected and weighted graphs, and graph density to map nodes to indices, interpret A[i][j] values and symmetry, and reason about the O(1) checks vs O(n^2) space trade-offs.

🔥 Graph → Understanding the graph data structure depends on the intro’s definitions (nodes, edges), graph types (directed/undirected, weighted/unweighted, dense/sparse), standard representations (adjacency lists/matrices), and baseline traversal/shortest‑path techniques (BFS, DFS) needed to specify, implement, and use graphs correctly.

🔥 Adjacency List → Understanding graph basics (nodes/edges, direction, weights, sparsity, and neighbors) is required to define an adjacency-list structure, interpret its entries, and evaluate its trade-offs for traversal and path algorithms.

🔥 Breadth First Search → BFS assumes understanding of nodes/edges, directed vs. undirected graphs, and common graph representations (adjacency lists/matrices) to correctly traverse levels and manage visited state.

🌟 Introduction To Weighted Graphs →

⚡️ Graph Traversal →

⚡️ Directed Acyclic Graph →

⚡️ Minimum Spanning Tree →

⚡️ Depth First Search →

⚡️ Undirected Graph →

⚡️ Graph Cost →

Network Flow →

Social Network Analysis →

Pagerank And Centrality →

Topological Sorting →

Dynamic Programming On Graphs →

Connectivity And Components →

Graph Representations →

Directed Graph →