354 - Knowledge Graphs in Python Using NetworkX library

Building and Analyzing Knowledge Graphs with NetworkX in Python In this tutorial, we dive into creating and analyzing knowledge graphs using the Python library NetworkX. Learn how to build meaningful graphs, add semantic attributes, and perform insightful analyses for real-world applications. This video covers: Graph Basics: Adding nodes and edges, and visualizing them with Matplotlib. Transforming Graphs into Knowledge Graphs: Adding attributes to nodes and edges for richer semantic meaning. Practical Example: Building a learning path for Python tutorials as a knowledge graph. Graph Analysis: Finding the number of nodes and edges. Calculating centrality to identify influential nodes. Checking graph connectivity. Shortest path computation. Community detection to identify clusters or groups. Path analysis and cycle detection for deeper insights. Code from the tutorial: https://github.com/bnsreenu/python_for_microscopists/blob/master/354_knowledge_graphs_using_NetworkX.ipynb