Explore a comprehensive 40-minute video walkthrough of a Graph Attention Network (GAT) project implementation. Dive into the Cora dataset, learn about a highly-optimized GAT implementation, and discover other exciting deep learning projects. Follow along as the instructor covers node degree statistics, entropy histograms, t-SNE plots, and graph drawing layouts. Gain insights into the Cora dataset, feature vectors, labels, and edge index construction. Understand the implementation through a toy example, explore lifting techniques, and grasp neighborhood-aware softmax and aggregation methods. Perfect for those looking to deepen their understanding of GAT and its practical applications in deep learning.