🔧 Overcoming Python's Memory Limitations for Efficient Handling of Massive Datasets in Graph Neural Networks

Introduction: The Challenge of Scaling Graph Neural Networks


Graph Neural Networks (GNNs) have emerged as a powerful tool for modeling complex relationships in data, from social networks to molecular structures. However, as datasets grow into the tens or hundreds of gigabytes, Python—the lingua franca of machine learning—hits a memory wall. This...