What has changed in the past five years in the role and importance of generalists in data teams The post Range Over Depth: A Reflection on the Role of the Data Generalist appeared first on Towards Data Science.
Mariia Bulycheva discusses the transition from classic deep learning to GNNs for Zalando’s landing page. She explains the complexities of converting user logs into heterogeneous graphs, the “message passing” training process, and the technical pitfalls of graph data leakage. She…
Mariia Bulycheva discusses the transition from classic deep learning to GNNs for Zalando’s landing page. She explains the complexities of converting user logs into heterogeneous graphs, the “message passing” training process, and the technical pitfalls of graph data leakage. She…
Mariia Bulycheva discusses the transition from classic deep learning to GNNs for Zalando’s landing page. She explains the complexities of converting user logs into heterogeneous graphs, the “message passing” training process, and the technical pitfalls of graph data leakage. She…
Mariia Bulycheva discusses the transition from classic deep learning to GNNs for Zalando’s landing page. She explains the complexities of converting user logs into heterogeneous graphs, the “message passing” training process, and the technical pitfalls of graph data leakage. She…
Mariia Bulycheva discusses the transition from classic deep learning to GNNs for Zalando’s landing page. She explains the complexities of converting user logs into heterogeneous graphs, the “message passing” training process, and the technical pitfalls of graph data leakage. She…
Mariia Bulycheva discusses the transition from classic deep learning to GNNs for Zalando’s landing page. She explains the complexities of converting user logs into heterogeneous graphs, the “message passing” training process, and the technical pitfalls of graph data leakage. She…
Mariia Bulycheva discusses the transition from classic deep learning to GNNs for Zalando’s landing page. She explains the complexities of converting user logs into heterogeneous graphs, the “message passing” training process, and the technical pitfalls of graph data leakage. She…
Mariia Bulycheva discusses the transition from classic deep learning to GNNs for Zalando’s landing page. She explains the complexities of converting user logs into heterogeneous graphs, the “message passing” training process, and the technical pitfalls of graph data leakage. She…
Mariia Bulycheva discusses the transition from classic deep learning to GNNs for Zalando’s landing page. She explains the complexities of converting user logs into heterogeneous graphs, the “message passing” training process, and the technical pitfalls of graph data leakage. She…
