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更新于 : Apr 05, 2016
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
Apr 2016
Trial ? 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。

Predictive analytics are used in more and more products, often directly in end user-facing functionality. H2O is an interesting open source package (with a startup behind it) that makes predictive analytics accessible to development teams, offering straightforward use of a wide variety of analytics, great performance and easy integration on JVM-based platforms. At the same time it integrates with the data scientists’ favorite tools, R and Python, as well as Hadoop and Spark.

Nov 2015
Trial ? 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。

Predictive analytics are used in more and more products, often directly in end user-facing functionality. H2O is an interesting open source package (with a startup behind it) that makes predictive analytics accessible to development teams, offering straightforward use of a wide variety of analytics, great performance and easy integration on JVM-based platforms. At the same time it integrates with the data scientists’ favorite tools, R and Python, as well as Hadoop and Spark.

May 2015
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

Predictive analytics are used in more and more products, often directly in end-user facing functionality. H2O is an interesting new open source package (with a startup behind it) that makes predictive analytics accessible to project teams due to its easy-to-use user interface. At the same time it integrates with the data scientists’ favourite tools, R and Python, as well as Hadoop and Spark. It offers great performance and, in our experience, easy integration at runtime, especially on JVM-based platforms.

发布于 : May 05, 2015

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