Accelerated Machine Learning with Google Cloud and NVIDIA

This hands-on lab demonstrates how to use NVIDIA cuDF and cuML within a Google Cloud Colab Enterprise environment to dramatically accelerate end-to-end machine learning workflows with zero code changes.

• Set up a cloud environment: Configure and connect to a GPU-accelerated runtime using Colab Enterprise runtime templates.
• Accelerate your pipeline instantly: Use cuDF and cuML to accelerate standard pandas data preparation and scikit-learn model training code without modification.
• Train models faster: Use GPU-accelerated algorithms including XGBoost, RandomForest, and LinearRegression to predict outcomes on large datasets.
• Benchmark and profile performance: Compare end-to-end execution times between CPU and GPU, and use profiling magic commands to identify execution fallbacks.

Speed up your pandas and scikit-learn machine learning workflows by up to an order of magnitude on Google Cloud’s Colab Enterprise using NVIDIA GPUs. With zero code rewrites, just a single extension-loading command.