PyData NYC 2018: End-to-End Data Science Without Leaving the GPU
Read OriginalThis article revisits a 2018 PyData NYC talk demonstrating a complete GPU-accelerated data science pipeline. It covers the OmniSci database and GPU dataframes (now cudf), explaining core concepts that remain valid. It includes updated setup instructions using conda to install pymapd and cudf, encouraging readers to use the provided Jupyter notebook for hands-on learning.
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