cuDF, cuML & RAPIDS: GPU Accelerated Data Science with Paul Mahler - TWiML Talk #254

This article discusses NVIDIA's RAPIDS open-source project, focusing on its subprojects like cuDF and cuML. It highlights the project's goal of accelerating traditional data science workflows and machine learning tasks using GPUs. The conversation with Paul Mahler, a senior data scientist at NVIDIA, delves into the RAPIDS ecosystem, including lower-level libraries and its relationship with other open-source projects such as Scikit-learn and XGBoost. The article provides a good overview of the project's components and its potential impact on data science.

• •RAPIDS aims to accelerate data science workflows using GPUs.
• •cuDF and cuML are key subprojects within the RAPIDS ecosystem.
• •The project integrates with other open-source libraries like Scikit-learn and XGBoost.