spd ukraine
概述
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总部
乌克兰
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成立年份
2006
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公司类型
私营公司
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收入
< $10m
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员工人数
201 - 1,000
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网站
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公司介绍
SPD-Ukraine 是一个技术社区，不仅是拥有共同价值观并坚信伟大的软件应该与优秀的人一起开发的技术人员。我们开发的产品被提名并授予 SIIA CODIE 和 GeekWire 奖。公司是一家负责任的企业，我们所有的活动都基于透明和诚信。我们始终忠于我们的原则和价值观——与我们的客户和合作伙伴合作，与我们的同事合作，并与不同的社区互动。
物联网解决方案
研究、技术咨询和软件产品开发服务，在预算内按时交付您的产品
技术栈
spd ukraine的技术栈描绘了spd ukraine在分析与建模等物联网技术方面的实践。
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设备层
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边缘层
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云层
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应用层
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配套技术
技术能力:
无
弱
中等
强
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DataRobot
DataRobot offers a Machine Learning platform for data scientists of all skill levels to build and deploy accurate predictive models in a fraction of the time it used to take. The technology addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics.The DataRobot platform uses massively parallel processing to train and evaluate 1000's of models in R, Python, Spark MLlib, H2O and other open-source libraries. It searches through millions of possible combinations of algorithms, pre-processing steps, features, transformations, and tuning parameters to deliver the best models for your dataset and prediction target. The DataRobot platform evaluates hundreds of cutting-edge Machine Learning algorithms to discover, deploy, and customize the best Machine Learning models for every situation. It also delivers the most accurate insights at scale, providing the fastest path to Data Science success for organizations of all sizes. DataRobot was founded in June 2012 and is headquartered in Boston, Massachusetts, USA.
Supplier
DeepMind
Founded by Demis Hassabis, Shane Legg and Mustafa Suleyman in London, 2010. DeepMind was supported by some of the most iconic tech entrepreneurs and investors of the past decade, prior to being acquired by Google in early 2014 in their largest European acquisition to date. The algorithms we build are capable of learning for themselves directly from raw experience or data, and are general in that they can perform well across a wide variety of tasks straight out of the box. Our world-class team consists of many renowned experts in their respective fields, including but not limited to deep neural networks, reinforcement learning and systems neuroscience-inspired models.
