Bring Accelerated Computing to Data Science in Python

With datasets growing rapidly in volume, velocity, and veracity, the demand for more efficient data processing has never been higher. This lab walks through how to apply open-source GPU accelerators from the NVIDIA RAPIDS project for common Python data science workflows.
Prerequisite(s):

Experience with Python, ideally including Pandas and NumPy.
Experience working with Polars, NetworkX, and XGBoost a plus.