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Important
AI Runtime for single-node tasks is in Public Preview. The distributed training API for multi-GPU workloads remain in Beta.
These notebooks run classic machine learning tasks on AI Runtime. They show how to use GPU acceleration for traditional ML algorithms and time series forecasting, including XGBoost regression and probabilistic forecasting with GluonTS.
| Tutorial | Description |
|---|---|
| XGBoost model training | This notebook demonstrates how to train an XGBoost regression model on a single GPU. XGBoost can significantly benefit from GPU acceleration for large datasets. |
| Time series forecasting with GluonTS | This notebook demonstrates an end-to-end workflow for probabilistic time-series forecasting of electricity consumption data with GluonTS's DeepAR model on a serverless GPU cluster. It covers data ingestion, resampling, model training, prediction, visualization, and evaluation. |