From 06aba388c6c674eca9331636a3ff2ce0d04ca399 Mon Sep 17 00:00:00 2001 From: Hai Ning Date: Thu, 24 Jan 2019 10:09:31 -0500 Subject: [PATCH] Update azure-ml-with-nvidia-rapids.ipynb --- contrib/RAPIDS/azure-ml-with-nvidia-rapids.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/contrib/RAPIDS/azure-ml-with-nvidia-rapids.ipynb b/contrib/RAPIDS/azure-ml-with-nvidia-rapids.ipynb index 6440b720..da6fde15 100644 --- a/contrib/RAPIDS/azure-ml-with-nvidia-rapids.ipynb +++ b/contrib/RAPIDS/azure-ml-with-nvidia-rapids.ipynb @@ -20,7 +20,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The [RAPIDS](https://www.developer.nvidia.com/rapids) suite of software libraries from NVIDIA enables the execution of end-to-end data science and analytics pipelines entirely on GPUs. In many machine learning projects, a significant portion of the model training time is spent in setting up the data; this stage of the process is known as Extraction, Transformation and Loading, or ETL. By using the DataFrame API for ETL\u00c2\u00a0and GPU-capable ML algorithms in RAPIDS, data preparation and training models can be done in GPU-accelerated end-to-end pipelines without incurring serialization costs between the pipeline stages. This notebook demonstrates how to use NVIDIA RAPIDS to prepare data and train model\u00c2\u00a0in Azure.\n", + "The [RAPIDS](https://www.developer.nvidia.com/rapids) suite of software libraries from NVIDIA enables the execution of end-to-end data science and analytics pipelines entirely on GPUs. In many machine learning projects, a significant portion of the model training time is spent in setting up the data; this stage of the process is known as Extraction, Transformation and Loading, or ETL. By using the DataFrame API for ETL and GPU-capable ML algorithms in RAPIDS, data preparation and training models can be done in GPU-accelerated end-to-end pipelines without incurring serialization costs between the pipeline stages. This notebook demonstrates how to use NVIDIA RAPIDS to prepare data and train model in Azure.\n", " \n", "In this notebook, we will do the following:\n", " \n", @@ -406,4 +406,4 @@ }, "nbformat": 4, "nbformat_minor": 2 -} \ No newline at end of file +}