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H2O
来自开放百科 - 灰狐
(版本间的差异)
小 (→h2o.js) |
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==版本== | ==版本== | ||
− | *[https://github.com/h2oai/h2o-3 h2o-3] | + | *[https://github.com/h2oai/h2o-3 h2o-3] [https://github.com/h2oai/h2o-3/tree/master/h2o-docs/src h2o-3文档] [http://docs.huihoo.com/h2o/3/ 在线文档] |
− | *[https://github.com/h2oai/h2o-2 h2o-2] | + | *[https://github.com/h2oai/h2o-2 h2o-2] [https://github.com/h2oai/h2o-tutorials h2o-tutorials] |
==安装== | ==安装== | ||
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==H2O Flow== | ==H2O Flow== | ||
[https://github.com/h2oai/h2o-flow H2O Flow] | [https://github.com/h2oai/h2o-flow H2O Flow] | ||
+ | |||
+ | ==机器学习== | ||
+ | *[https://github.com/h2oai/deepwater/ Deep Water] [[Deep learning]] in H2O using Native [[GPU]] Backends | ||
+ | *[http://docs.huihoo.com/h2o/3/data-science/deep-learning.html H2O Deep Learning 文档] | ||
+ | |||
+ | ==项目== | ||
+ | [https://github.com/h2oai/awesome-h2o Awesome H2O] [[文件:awesome.png]] | ||
+ | |||
+ | ==文档== | ||
+ | *[http://docs.huihoo.com/knime/summits/knime-fall-summit-2017-austin/Integrating-high-performance-machine-learning-H2O-and-KNIME.pdf Integrating high performance machine learning: H2O and KNIME] | ||
+ | *[http://docs.huihoo.com/h2o/h2o-meetups/ 更多幻灯片>>>] | ||
==图集== | ==图集== | ||
<gallery> | <gallery> | ||
+ | image:Gartner-2018-Magic-Quadrant-for-Data-Science-and-Machine-Learning.png|Gartner魔力象限 | ||
+ | image:why-h2o.png|Why H2O | ||
+ | image:H2O-High-Level-Architecture.png|架构 | ||
+ | image:H2O-Distributed-Algorithms.png|分布式算法 | ||
image:H2O-Architecture-Slide.png|架构 | image:H2O-Architecture-Slide.png|架构 | ||
image:h2o-software-stack.png|软件堆栈 | image:h2o-software-stack.png|软件堆栈 | ||
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image:h2o-frame-data-structures.jpg|H2OFrame | image:h2o-frame-data-structures.jpg|H2OFrame | ||
image:h2o-spark-workflow.jpg|工作流 | image:h2o-spark-workflow.jpg|工作流 | ||
+ | image:h2o-run-glm-from-r.png|GLM处理流 | ||
image:h2o-flow.png|H2O Flow | image:h2o-flow.png|H2O Flow | ||
image:h2o-flow-model.png|模型 | image:h2o-flow-model.png|模型 | ||
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[[category:python]] | [[category:python]] | ||
[[category:spark]] | [[category:spark]] | ||
+ | [[category:storm]] | ||
[[category:hadoop]] | [[category:hadoop]] |
2018年3月17日 (六) 08:14的最后版本
您可以在Wikipedia上了解到此条目的英文信息 H2O Thanks, Wikipedia. |
h2o = fast statistical, machine learning & math runtime for big data
H2O是一个开源分布式的内存处理引擎用于机器学习和大数据,它拥有一个令人印象深刻的数组的算法,支持R、Python和Java语言,同时它也可以作为Apache Spark在后端的执行引擎。
使用H2O的最佳方式是把它作为R环境的一个大内存扩展,R环境并不直接作用于大的数据集,而是通过扩展通讯协议例如REST API与H2O集群通讯,H2O来处理大量的数据工作。
目录 |
[编辑] 简介
H2O - the killer app for Spark
[编辑] 版本
[编辑] 安装
curl -o h2o.zip http://download.h2o.ai/versions/h2o-3.8.1.4.zip unzip h2o.zip cd h2o-3.8.1.4 java -jar h2o.jar http://localhost:54321
[编辑] h2o.js
h2o.js: Node.js bindings to H2O
[编辑] H2O Flow
[编辑] 机器学习
- Deep Water Deep learning in H2O using Native GPU Backends
- H2O Deep Learning 文档
[编辑] 项目
[编辑] 文档
[编辑] 图集
[编辑] 链接
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