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发布于 : Apr 24, 2019
这一条目不在当前版本的技术雷达中。如果它出现在最近几期中,那么它很有可能仍然具有相关参考价值。如果这一条目出现在更早的雷达中,那么它很有可能已经不再具有相关性,我们的评估将不再适用于当下。很遗憾我们没有足够的带宽来持续评估以往的雷达内容。 了解更多
Apr 2019
Assess ? 在了解它将对你的企业产生什么影响的前提下值得探索

Data scientists and engineers often use libraries such as pandas to perform ad hoc data analysis. Although expressive and powerful, these libraries have one critical limitation: they only work on a single CPU and don't provide horizontal scalability for large data sets. Dask, however, includes a lightweight, high-performance scheduler that can scale from a laptop to a cluster of machines. And because it works with NumPy, pandas and Scikit-learn, Dask looks promising for further assessment.

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