Predicting Taxi Fare

In this lab you will familiarize yourself with RAPIDS GPU data frame library cuDF and how it integrates with Dask and XGBoost. You will use cuDF to ingest data into the GPU and then run data cleanup. This information will then be used to train an XGBoost model to predict the taxi fares in Manhattan.

To get started, open and run through the NYC Taxi Jupyter notebook to train an XGBoost model on the NYC Taxi data set. You will complete the remainder of this lab in the Juypter notebook.


To run a cell on the Jupyer notebook, click on the cell you want to run and press Shift + Enter. Linux bash commands can be run inside the Jupyter notebook by adding a bang symbol (!) before the command inside the Jupyter notebook cell.

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