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Unlocking the Power of Relational Data: Graph Theory in AI

Most Machine Learning courses teach you about grids (images) or sequences (text). but what about the messy, interconnected world of relationships? This 4-minute animation explains how Graph Theory bridges the gap.

In this video, we visualize:**
The Graph Structure**: Nodes, Edges, and the Adjacency Matrix.
The Data Problem**: Why standard neural networks struggle with social networks and molecules.
Message Passing**: The core intuition behind Graph Neural Networks (GNNs). "Tell me who your friends are, and I'll tell you who you are."
Real World Applications**: Breaking down complex networks.

Visualized with Manim and Python.

Timestamps:
0:00 - Intro: The World is a Graph
0:45 - Graph Basics & Matrices
1:30 - The Limit of Standard ML
2:15 - GNNs: The Message Passing Intuition
3:15 - Applications & Conclusion

#Tags
#AIForEveryone #GraphNeuralNetworks #GNN #GraphTheory #MachineLearning #Manim #Python #DataScience