Deep Learning (Python, C, C++, Java, Scala, Go)
Classes :
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DBN: Deep Belief Nets
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CDBN: Deep Belief Nets w/ continuous-valued inputs
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RBM: Restricted Boltzmann Machine
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CRBM: Restricted Boltzmann Machine w/ continuous-valued inputs
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dA: Denoising Autoencoders
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SdA: Stacked Denoising Autoencoders
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LogisticRegression: Logistic Regression
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HiddenLayer: Hidden Layer of Neural Networks
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MLP: Multiple Layer Perceptron
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Dropout: Dropout MLP
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CNN: Convolutional Neural Networks (See dev branch.)
References :
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Y. Bengio, P. Lamblin, D. Popovici, H. Larochelle: Greedy Layer-Wise Training of Deep Networks, Advances in Neural Information Processing Systems 19, 2007
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P. Vincent, H. Larochelle, Y. Bengio, P.A. Manzagol: Extracting and Composing Robust Features with Denoising Autoencoders, ICML' 08, 1096-1103, 2008
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DeepLearningTutorials https://github.com/lisa-lab/DeepLearningTutorials
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Yusuke Sugomori: Stochastic Gradient Descent for Denoising Autoencoders, http://yusugomori.com/docs/SGD_DA.pdf
Publication :
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More detailed Java implementations are introduced in my book, Java Deep Learning Essentials.
The book is available from Packt Publishing or Amazon.
Bug reports / contributions / donations are deeply welcome.
Bitcoin wallet address: 34kZarc2uBU6BMCouUp2iudvZtbmZMPqrA