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deep_learning_tutorial
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Update : 2015-05-29
Size : 20.71mb
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Author :
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Introduction - If you have any usage issues, please Google them yourself
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deep learning tutorial
Packet file list
(Preview for download)
deep_learning_tutorial\Efficient Learning of Sparse Representations with an Energy-Based Model.pdf
......................\learning deep architectures for AI.pdf
......................\RBM\A fast learning algorithm for deep belief nets.pdf
......................\...\A new learning algorithm for mean field boltzmann machines.pdf
......................\...\guideTR.pdf
......................\...\modeling image patches with a directed hierarchy of markov random fields.pdf
......................\...\NotesOnCD.pdf
......................\...\On Contrastive Divergence Learning.pdf
......................\...\Reducing the Dimensionality with DNN - science - supp.pdf
......................\...\Reducing the Dimensionality with DNN - science.pdf
......................\slidesBengio.pdf
......................\Stanford 教授 Andrew Ng 的 Deep Learning 教程\01.pdf
......................\.............................................\02.pdf
......................\.............................................\03.pdf
......................\.............................................\04.pdf
......................\.............................................\05.pdf
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......................\.............................................\11.pdf
......................\.............................................\12.pdf
......................\.............................................\13.pdf
......................\.............................................\14.pdf
......................\.............................................\15.pdf
......................\.............................................\16.pdf
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......................\.............................................\21.pdf
......................\.............................................\22.pdf
......................\.............................................\23.pdf
......................\.............................................\24.pdf
......................\.............................................\25.pdf
......................\.............................................\26.pdf
......................\Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition.pdf
......................\What Regularized Auto-Encoders Learn from the Data Generating Distribut....pdf
......................\RBM
......................\Stanford 教授 Andrew Ng 的 Deep Learning 教程
deep_learning_tutorial
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