cuml-machine-learning

What problem does it solve?

This Skill accelerates machine learning tasks on large tabular datasets by leveraging the power of NVIDIA GPUs with the cuML library.

Core Features & Use Cases

• GPU-accelerated ML: Perform classification, regression, clustering, and dimensionality reduction tasks significantly faster.
• Scikit-learn compatible API: Easily integrate GPU acceleration into existing ML workflows.
• Use Case: Train a Random Forest classifier on a dataset with millions of rows and thousands of features in minutes instead of hours.

Quick Start

Use the cuml-machine-learning skill to train a RandomForestClassifier on the provided dataset, splitting it into training and testing sets with a 0.2 test size.