The RAPIDS Notebooks Extended repository includes several examples with end-to-end examples using Dask for distributed, GPU-accelerated computation. Here’s a few from the collection to get started with.
The Introductino to Dask shows how to get started with Dask using basic Python primitives like integers and strings. Go to notebook
Introduction to XGBoost with RAPIDS shows the acceleration one can gain by using GPUs with XGBoost in RAPIDS. Go to notebook
The Linear Regression with Dask+cuML shows a simple example of how to get started with distributed machine learning. Go to notebook
The NYC Taxi End-to-End notebook uses trip data to predict New York City taxi fares (a regression problem). Go to notebook