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Deeplearning4j
来自开放百科 - 灰狐
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==DL4J[http://deeplearning4j.org/neuralnet-overview 神经网络]== | ==DL4J[http://deeplearning4j.org/neuralnet-overview 神经网络]== | ||
[http://deeplearning4j.org/neuralnetworktable.html 如何选择神经网络] | [http://deeplearning4j.org/neuralnetworktable.html 如何选择神经网络] | ||
− | *[ | + | *[https://deeplearning4j.org/cn/restrictedboltzmannmachine 受限玻尔兹曼机] |
− | *[ | + | *[https://deeplearning4j.org/cn/convolutionalnets 卷积网络](图像) |
− | *[ | + | *[https://deeplearning4j.org/cn/lstm 递归网络/LSTMs](时间序列和传感器数据) |
− | *[https:// | + | *[https://deeplearning4j.org/cn/deepbeliefnetwork 深度置信网络] |
− | *[ | + | *[https://deeplearning4j.org/cn/deepautoencoder 深度自动编码器](问答、数据压缩) |
− | *[ | + | *[https://deeplearning4j.org/cn/usingrnns 递归神经传感器网络](场景、分析) |
− | + | *[https://deeplearning4j.org/cn/stackeddenoisingautoencoder 堆叠式降噪自动编码器] | |
− | *[ | + | *[https://github.com/deeplearning4j/rl4j 深度增强学习] |
==为何选择DL4J== | ==为何选择DL4J== | ||
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==指南== | ==指南== | ||
+ | git clone https://github.com/deeplearning4j/dl4j-0.4-examples.git | ||
+ | cd dl4j-0.4-examples/ | ||
+ | mvn clean install | ||
+ | 使用 [[IntelliJ IDEA]] 打开项目,[http://deeplearning4j.org/quickstart.html 完成DL4J第一次体验]。 | ||
==推荐引擎== | ==推荐引擎== | ||
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==[[Apache Spark|Spark]]== | ==[[Apache Spark|Spark]]== | ||
− | *[ | + | *[https://deeplearning4j.org/cn/spark 基于Spark的Deeplearning4j] |
− | *[ | + | *[https://deeplearning4j.org/cn/iterativereduce DL4J与基于Hadoop和Spark的迭代式归纳] |
*[http://deeplearning4j.org/spark-fast-native-binaries.html How to Speed Up Spark With Native Binaries and OpenBlas] | *[http://deeplearning4j.org/spark-fast-native-binaries.html How to Speed Up Spark With Native Binaries and OpenBlas] | ||
+ | |||
+ | ==Kotlin== | ||
+ | [https://deeplearning4j.org/kotlin Using Deeplearning4j With Kotlin] | ||
+ | |||
+ | ==Scala== | ||
+ | [https://deeplearning4j.org/scala Scala, Apache Spark and Deeplearning4j] | ||
+ | *[https://github.com/deeplearning4j/ScalNet ScalNet]是受[[Keras]]启发而为Deeplearning4j开发的[[Scala]]语言封装 | ||
+ | *[https://github.com/deeplearning4j/nd4s ND4S] Scala bindings for [[ND4J]] | ||
+ | |||
+ | ==Clojure== | ||
+ | [https://deeplearning4j.org/clojure Deep Learning With Clojure] | ||
+ | |||
+ | ==[[C++]]== | ||
+ | *[[JavaCPP]] | ||
==图集== | ==图集== | ||
<gallery> | <gallery> | ||
image:deeplearning4j-overview.png|DL4J | image:deeplearning4j-overview.png|DL4J | ||
+ | image:dl4j-eco-cn.jpg|DL4J组件 | ||
image:deep-learning-use-case-industries.png|工业应用 | image:deep-learning-use-case-industries.png|工业应用 | ||
image:deeplearning4j-ui.png|DL4J UI | image:deeplearning4j-ui.png|DL4J UI | ||
+ | image:deeplearning4j-training-ui.png|训练UI | ||
image:neural-network-table.png|神经网络 | image:neural-network-table.png|神经网络 | ||
+ | image:Deeplearning4j-Reference-Architecture-CPU-GPU-Training.png|DL4J参考架构:训练 | ||
+ | image:Deeplearning4j-Reference-Architecture-CPU-GPU-Scoring.png|DL4J参加架构:得分 | ||
+ | image:SKIL-Reference-Architecture.png|SKIL参考架构 | ||
</gallery> | </gallery> | ||
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*[http://docs.huihoo.com/javadoc/deeplearning4j/ deeplearning4j javadoc] | *[http://docs.huihoo.com/javadoc/deeplearning4j/ deeplearning4j javadoc] | ||
*[http://deeplearning4j.org/glossary 深度学习词汇表] | *[http://deeplearning4j.org/glossary 深度学习词汇表] | ||
+ | *[http://deeplearning4j.org/compare-dl4j-torch7-pylearn.html DL4J vs. Torch vs. Theano vs. Caffe vs. TensorFlow] | ||
*[http://skymind.io/ Skymind]是DL4J的商业支持机构 | *[http://skymind.io/ Skymind]是DL4J的商业支持机构 | ||
[[category:deep learning]] | [[category:deep learning]] | ||
[[category:neural network]] | [[category:neural network]] | ||
+ | [[category:recommender system]] | ||
[[category:hadoop]] | [[category:hadoop]] | ||
[[category:spark]] | [[category:spark]] | ||
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[[category:scala]] | [[category:scala]] | ||
[[category:clojure]] | [[category:clojure]] | ||
+ | [[category:huihoo]] |
2017年12月19日 (二) 08:50的版本
deeplearning4j:开源(Apache v2)神经网络平台,基于 Apache Hadoop, Apache Spark 构建,为 Java, Scala & Clojure 编程语言提供的深度学习库。
目录 |
应用场景
神经网络应用情景
DL4J神经网络
- 受限玻尔兹曼机
- 卷积网络(图像)
- 递归网络/LSTMs(时间序列和传感器数据)
- 深度置信网络
- 深度自动编码器(问答、数据压缩)
- 递归神经传感器网络(场景、分析)
- 堆叠式降噪自动编码器
- 深度增强学习
为何选择DL4J
为何选择Deeplearning4j?
- 功能多样的N维数组类,为Java和Scala设计
- 与GPU集合
- 可在Hadoop、Spark上实现伸缩
- Canova:机器学习库的通用向量化工具
- ND4J:线性代数库,较Numpy快一倍
- 文档全面、有深度、多语言
指南
git clone https://github.com/deeplearning4j/dl4j-0.4-examples.git cd dl4j-0.4-examples/ mvn clean install
使用 IntelliJ IDEA 打开项目,完成DL4J第一次体验。
推荐引擎
Build a Recommendation Engine With DL4J
Spark
- 基于Spark的Deeplearning4j
- DL4J与基于Hadoop和Spark的迭代式归纳
- How to Speed Up Spark With Native Binaries and OpenBlas
Kotlin
Using Deeplearning4j With Kotlin
Scala
Scala, Apache Spark and Deeplearning4j
Clojure
C++
图集
链接
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