“第十七章 深度学习”版本间的差异

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==视频展示==
 
==视频展示==
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*VGG Net visualization [http://aigraph.cslt.org/courses/17/VGG16.mp4]
  
 
==演示链接==
 
==演示链接==
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==高级读者==
 
==高级读者==
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* LeCun Y, Bengio Y, Hinton G. Deep learning[J]. nature, 2015, 521(7553): 436-444.[https://s3.us-east-2.amazonaws.com/hkg-website-assets/static/pages/files/DeepLearning.pdf]
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* Krizhevsky A, Sutskever I, Hinton G E. Imagenet classification with deep convolutional neural networks[J]. Advances in neural information processing systems, 2012, 25. [https://proceedings.neurips.cc/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf]
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* Hinton G E, Salakhutdinov R R. Reducing the dimensionality of data with neural networks[J]. science, 2006, 313(5786): 504-507. [https://asset-pdf.scinapse.io/prod/2100495367/2100495367.pdf]
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* Hinton G E, Osindero S, Teh Y W. A fast learning algorithm for deep belief nets[J]. Neural computation, 2006, 18(7): 1527-1554. [https://www.cs.utoronto.ca/~hinton/absps/ncfast.pdf]
  
 
* 王东,机器学习导论,第三章,神经模型,2021,清华大学出版社 [http://mlbook.cslt.org]
 
* 王东,机器学习导论,第三章,神经模型,2021,清华大学出版社 [http://mlbook.cslt.org]
 
* Ian Goodfellow and Yoshua Bengio and Aaron Courville, Deep Learning [https://www.deeplearningbook.org/]
 
* Ian Goodfellow and Yoshua Bengio and Aaron Courville, Deep Learning [https://www.deeplearningbook.org/]

2022年8月5日 (五) 10:42的版本

教学资料

  • 教学参考
  • 课件
  • 小清爱提问:什么是深度学习(上)?[1]
  • 小清爱提问:什么是深度学习(下)?[2]

扩展阅读

视频展示

  • VGG Net visualization [3]

演示链接

  • ConvNetJS 深度神经网络演示 [4]
  • Leiden Demo for image classification [5]
  • CNN explainer[6]
  • Quick style transfer [7]
  • Pix2Pix[8]
  • AutoWriter[9]

开发者资源

  • Georgia Tech, Polo Club (可解释机器学习) [10]
  • Google developer courses [11]
  • ConvNetJS 代码 [12]

高级读者

  • LeCun Y, Bengio Y, Hinton G. Deep learning[J]. nature, 2015, 521(7553): 436-444.[13]
  • Krizhevsky A, Sutskever I, Hinton G E. Imagenet classification with deep convolutional neural networks[J]. Advances in neural information processing systems, 2012, 25. [14]
  • Hinton G E, Salakhutdinov R R. Reducing the dimensionality of data with neural networks[J]. science, 2006, 313(5786): 504-507. [15]
  • Hinton G E, Osindero S, Teh Y W. A fast learning algorithm for deep belief nets[J]. Neural computation, 2006, 18(7): 1527-1554. [16]
  • 王东,机器学习导论,第三章,神经模型,2021,清华大学出版社 [17]
  • Ian Goodfellow and Yoshua Bengio and Aaron Courville, Deep Learning [18]