RAPIDS cuGraph
The Data Scientist has a collection of techniques within their proverbial toolbox. Data engineering, statistical analysis, and machine learning are among the most commonly known. However, there are numerous cases where the focus of the analysis is on the relationship between data elements. In those cases, the data is... Read more
The Rise of Notebooks Extended
I recently had the privilege of presenting a workshop at the AI + Education Curiosity Conference 2019. There, I demonstrated to educators, school district staff, researchers, and students how RAPIDS software enables students to learn and iteratively practice data science using full datasets all within classroom time constraints. Compared to current methods and workarounds,... Read more
Run RAPIDS on Google Colab — For Free
Google Colab is a hosted Jupyter-Notebook like service which has long offered free access to GPU instances. Recently, Colab got even sweeter. The GPUs powering Colab were upgraded to NVIDIA new T4 GPUs. This upgrade unlocks new software packages; which means you can now experiment with RAPIDS on Colab for free! Check out... Read more
Using RAPIDS with PyTorch
In this post we take a look at how to use cuDF, the RAPIDS dataframe library, to do some of the preprocessing steps required to get the mortgage data in a format that PyTorch can process so that we can explore the performance of deep learning on tabular data and... Read more