We were recently joined by Holden Karau, Spark maintainer and former Princess of the Covariance Matrix (long story), for a discussion on the design of Dask, how it compares to PySpark, and why these tradeoffs were chosen.
Lots of people talk about “democratizing” data science and machine learning. what could be more democratic — in the sense of widely accessible — than SQL, PyData, and scaling data science to larger datasets and models?
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