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Last updated : Nov 30, 2017
不在本期内容中
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
Nov 2017
试验 ? 值得一试。了解为何要构建这一能力是很重要的。企业应当在风险可控的前提下在项目中尝试应用此项技术。

Scikit-learn is not a new tool (it is approaching its tenth birthday); what is new is the rate of adoption of machine-learning tools and techniques outside of academia and major tech companies. Providing a robust set of models and a rich set of functionality, Scikit-learn plays an important role in making machine-learning concepts and capabilities more accessible to a broader (and often non-expert) audience.

Nov 2016
评估 ? 在了解它将对你的企业产生什么影响的前提下值得探索

Scikit-learn is an increasingly popular machine-learning library written in Python. It provides a robust set of machine-learning models such as clustering, classification, regression and dimensionality reduction, and a rich set of functionality for companion tasks like model selection, model evaluation and data preparation. Since it is designed to be simple, reusable in various contexts and well documented, we see this tool accessible even to nonexperts to explore the machine-learning space.

已发布 : Nov 07, 2016
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