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Learn the fundamentals of graph theory and knowledge graphs in this 27-minute tutorial that explores core concepts, applications, and analytical metrics. Discover the essential differences between regular graphs and knowledge graphs while understanding how nodes and edges represent relationships between objects in real-world scenarios like social networks and road maps. Master key graph metrics including centrality measures, community detection techniques, and path analysis methods for extracting meaningful insights from network structures. Explore practical applications in route planning, recommendation systems, and social network analysis, while getting introduced to tools for knowledge graph representation, including NetworkX Python library. Gain foundational knowledge necessary for implementing graph-based solutions in modern AI, machine learning, and data visualization applications.
