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@@ -48,6 +48,8 @@
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3. [Deep Learning for NLP (without Magic)](http://www.socher.org/index.php/DeepLearningTutorial/DeepLearningTutorial)
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4. [A Deep Learning Tutorial: From Perceptrons to Deep Networks](http://www.toptal.com/machine-learning/an-introduction-to-deep-learning-from-perceptrons-to-deep-networks)
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5. [Deep Learning from the Bottom up](http://www.metacademy.org/roadmaps/rgrosse/deep_learning)
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+6. [Theano Tutorial](http://deeplearning.net/tutorial/deeplearning.pdf)
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+
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### WebSites
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@@ -71,6 +73,7 @@
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2. [Torch7](http://torch.ch/)
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3. [Theano](http://deeplearning.net/software/theano/)
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4. [cuda-convnet](https://code.google.com/p/cuda-convnet2/)
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+5. [convetjs](https://github.com/karpathy/convnetjs)
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5. [Ccv](http://libccv.org/doc/doc-convnet/)
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6. [NuPIC](http://numenta.org/nupic.html)
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7. [DeepLearning4J](http://deeplearning4j.org/)
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@@ -78,6 +81,10 @@
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9. [DeepLearnToolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox)
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10. [Deepnet](https://github.com/nitishsrivastava/deepnet)
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11. [Deeppy](https://github.com/andersbll/deeppy)
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+12. [JavaNN](https://github.com/ivan-vasilev/neuralnetworks)
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+13. [hebel](https://github.com/hannes-brt/hebel)
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+14. [Mocha.jl](https://github.com/pluskid/Mocha.jl)
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+15. [OpenDL](https://github.com/guoding83128/OpenDL)
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### Miscellaneous
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