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Artificial neural network
来自开放百科 - 灰狐
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Artificial neural network (ANN) 人工神经网络 | Artificial neural network (ANN) 人工神经网络 | ||
| − | [[convolutional neural network|卷积神经网络]] | + | ==类型== |
| + | *[[convolutional neural network|卷积神经网络]] | ||
| + | *[[Deep belief network|深度信念网络]] | ||
==项目== | ==项目== | ||
*[http://deeplearning4j.org/zh-word2vec.html Word2vec]是一个神经网络，它用来在使用深度学习算法之前预处理文本。它本身并没有实现深度学习，但是Word2Vec把文本变成深度学习能够理解的向量形式。 | *[http://deeplearning4j.org/zh-word2vec.html Word2vec]是一个神经网络，它用来在使用深度学习算法之前预处理文本。它本身并没有实现深度学习，但是Word2Vec把文本变成深度学习能够理解的向量形式。 | ||
*[[Deeplearning4j]], [http://deeplearning4j.org/neuralnetworktable.html 如何选择神经网络], [http://deeplearning4j.org/neuralnet-overview Introduction to Deep Neural Networks] | *[[Deeplearning4j]], [http://deeplearning4j.org/neuralnetworktable.html 如何选择神经网络], [http://deeplearning4j.org/neuralnet-overview Introduction to Deep Neural Networks] | ||
| + | *[https://github.com/ivan-vasilev/neuralnetworks JavaNN] | ||
*[[emergent]] | *[[emergent]] | ||
| + | *[https://developer.nvidia.com/cuDNN cuDNN] | ||
| + | *[https://circuit-gnn.csail.mit.edu/ Circuit-GNN] Graph Neural Networks for Distributed Circuit Design | ||
| + | *[https://github.com/MolecularAI/GraphINVENT GraphINVENT] Graph neural networks for molecular design. | ||
==文档== | ==文档== | ||
| + | *[http://docs.huihoo.com/deep-learning/deeplearningsummerschool/2015/Multilayer-Neural-Networks.pdf Multilayer Neural Networks] | ||
| + | *[http://docs.huihoo.com/deep-learning/deeplearningsummerschool/2015/Training-Deep-Neural-Networks.pdf Training Deep Neural Networks] | ||
| + | *[http://docs.huihoo.com/deep-learning/Artificial-Neural-Networks-and-Deep-Learning--Slides-zh-CN-20151227.pdf 神经网络与深度学习-幻灯片] | ||
| + | *[http://docs.huihoo.com/deep-learning/Artificial-Neural-Networks-and-Deep-Learning-Notes-zh-CN-20151211.pdf 神经网络与深度学习-讲义] | ||
*[http://docs.huihoo.com/infoq/qconshanghai/2015/%e5%9f%ba%e4%ba%8e%e5%a4%a7%e6%95%b0%e6%8d%ae%e7%9a%84%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0%e6%8a%80%e6%9c%af/QCon%e4%b8%8a%e6%b5%b72015-%e5%9c%a8Spark%e4%b8%8a%e6%9e%84%e5%bb%ba%e7%a1%ac%e4%bb%b6%e5%8a%a0%e9%80%9f%e7%9a%84%e5%88%86%e5%b8%83%e5%bc%8f%e7%a5%9e%e7%bb%8f%e7%bd%91%e7%bb%9c%e6%9e%b6%e6%9e%84-%e7%8e%8b%e5%a5%95%e6%81%92%e3%80%81%e9%bb%84%e6%99%9f%e7%9b%9b.pdf 在Spark上构建分布式神经网络] | *[http://docs.huihoo.com/infoq/qconshanghai/2015/%e5%9f%ba%e4%ba%8e%e5%a4%a7%e6%95%b0%e6%8d%ae%e7%9a%84%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0%e6%8a%80%e6%9c%af/QCon%e4%b8%8a%e6%b5%b72015-%e5%9c%a8Spark%e4%b8%8a%e6%9e%84%e5%bb%ba%e7%a1%ac%e4%bb%b6%e5%8a%a0%e9%80%9f%e7%9a%84%e5%88%86%e5%b8%83%e5%bc%8f%e7%a5%9e%e7%bb%8f%e7%bd%91%e7%bb%9c%e6%9e%b6%e6%9e%84-%e7%8e%8b%e5%a5%95%e6%81%92%e3%80%81%e9%bb%84%e6%99%9f%e7%9b%9b.pdf 在Spark上构建分布式神经网络] | ||
| + | *[http://docs.huihoo.com/deep-learning/Recursive-Deep-Learning-for-Natural-Language-Processing-and-Computer-Vision.pdf Recursive Deep Learning for Natural Language Processing and Computer Vision] | ||
| + | *[http://docs.huihoo.com/deep-learning/Training-Recurrent-Neural-Networks.pdf Training Recurrent Neural Networks] | ||
| + | *[http://docs.huihoo.com/deep-learning/Statistical-Language-Models-based-on-Neural-Networks.pdf Statistical Language Models based on Neural Networks] | ||
| + | *[http://docs.huihoo.com/deep-learning/Supervised-Sequence-Labelling-with-Recurrent-Neural-Networks.pdf Supervised Sequence Labelling with Recurrent Neural Networks] | ||
| + | *[http://docs.huihoo.com/gputechconf/gtc2015/S5552-Transparent-Parallelization-of-Neural-Network-Training.pdf Transparent parallelization of neural network training] | ||
| + | *[http://docs.huihoo.com/gputechconf/gtc2015/S5571-A-High-Density-GPU-Solution-for-DNN-Training.pdf A High-Density GPU Solution for DNN Training] | ||
| + | |||
| + | ==图集== | ||
| + | <gallery> | ||
| + | image:Neural-Network-and-Deep-Learning.png|神经网络与深度学习 | ||
| + | image:neural-network-table.png|神经网络 | ||
| + | image:popular-deep-learning-models.png|深度学习模型 | ||
| + | image:neural-network-zoo.png|神经网络Zoo | ||
| + | image:graph-neural-networks.png|图神经网络 | ||
| + | </gallery> | ||
==链接== | ==链接== | ||
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[[category:neural network]] | [[category:neural network]] | ||
| + | [[category:deep learning]] | ||
[[category:artificial intelligence]] | [[category:artificial intelligence]] | ||
2022年8月7日 (日) 11:54的最后版本
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您可以在Wikipedia上了解到此条目的英文信息 Artificial neural network Thanks, Wikipedia. |
Artificial neural network (ANN) 人工神经网络
目录 |
[编辑] 类型
[编辑] 项目
- Word2vec是一个神经网络，它用来在使用深度学习算法之前预处理文本。它本身并没有实现深度学习，但是Word2Vec把文本变成深度学习能够理解的向量形式。
- Deeplearning4j, 如何选择神经网络, Introduction to Deep Neural Networks
- JavaNN
- emergent
- cuDNN
- Circuit-GNN Graph Neural Networks for Distributed Circuit Design
- GraphINVENT Graph neural networks for molecular design.
[编辑] 文档
- Multilayer Neural Networks
- Training Deep Neural Networks
- 神经网络与深度学习-幻灯片
- 神经网络与深度学习-讲义
- 在Spark上构建分布式神经网络
- Recursive Deep Learning for Natural Language Processing and Computer Vision
- Training Recurrent Neural Networks
- Statistical Language Models based on Neural Networks
- Supervised Sequence Labelling with Recurrent Neural Networks
- Transparent parallelization of neural network training
- A High-Density GPU Solution for DNN Training
[编辑] 图集
神经网络与深度学习
神经网络
深度学习模型
神经网络Zoo
图神经网络
[编辑] 链接
- Comparison of Neural Network Simulators
- Awesome Recurrent Neural Networks
- colah's blog: Neural Networks, Visualizing Neural Networks, Convolutional Neural Networks
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