cuml-machine-learning

What problem does it solve?

This Skill enables rapid machine learning model training and inference on large tabular datasets by leveraging the power of NVIDIA GPUs, significantly reducing processing time compared to CPU-based methods.

Core Features & Use Cases

• GPU Acceleration: Utilizes NVIDIA cuML for high-performance machine learning.
• Scikit-learn Compatible API: Familiar interface for classification, regression, clustering, and dimensionality reduction.
• Use Case: Train a Random Forest classifier on a dataset with millions of rows and thousands of features in minutes instead of hours, or perform PCA on high-dimensional data for visualization.

Quick Start

Use the cuml-machine-learning skill to train a RandomForestClassifier on the provided dataset, splitting it into training and testing sets with 80% for training.