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Recognition](http://nlp.stanford.edu/~socherr/pa4_ner.pdf) [zip](http://nlp.stanford.edu/~socherr/pa4-ner.zip)
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6. [Training tricks by YB](http://www.iro.umontreal.ca/~bengioy/papers/YB-tricks.pdf)
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7. [Geoff Hinton's reading list (all papers)] (http://www.cs.toronto.edu/~hinton/deeprefs.html)
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+8. [Supervised Sequence Labelling with Recurrent Neural Networks](http://www.cs.toronto.edu/~graves/preprint.pdf)
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+9. [Statistical Language Models based on Neural Networks](http://www.fit.vutbr.cz/~imikolov/rnnlm/thesis.pdf)
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+10. [Training Recurrent Neural Networks](http://www.cs.utoronto.ca/~ilya/pubs/ilya_sutskever_phd_thesis.pdf)
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+11. [Recursive Deep Learning for Natural Language Processing and Computer Vision](http://nlp.stanford.edu/~socherr/thesis.pdf)
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+12. Bi-directional RNN [(http://www.di.ufpe.br/~fnj/RNA/bibliografia/BRNN.pdf)]
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+13. LSTM [(http://web.eecs.utk.edu/~itamar/courses/ECE-692/Bobby_paper1.pdf)]
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+14. GRU (Gated Recurrent Unit) [[Paper](http://arxiv.org/pdf/1406.1078v3.pdf)]
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+15. GFRNN [(http://arxiv.org/pdf/1502.02367v3.pdf)] [.](http://jmlr.org/proceedings/papers/v37/chung15.pdf) [.](http://jmlr.org/proceedings/papers/v37/chung15-supp.pdf)
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### Tutorials
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@@ -68,7 +77,6 @@ Recognition](http://nlp.stanford.edu/~socherr/pa4_ner.pdf) [zip](http://nlp.stan
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### WebSites
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1. [deeplearning.net](http://deeplearning.net/)
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@@ -100,6 +108,12 @@ Recognition](http://nlp.stanford.edu/~socherr/pa4_ner.pdf) [zip](http://nlp.stan
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6. [Flickr Data](http://yahoolabs.tumblr.com/post/89783581601/one-hundred-million-creative-commons-flickr-images) 100 Million Yahoo dataset
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7. [Berkeley Segmentation Dataset 500](http://www.eecs.berkeley.edu/Research/Projects/CS/vision/bsds/)
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8. [UC Irvine Machine Learning Repository](http://archive.ics.uci.edu/ml/)
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+9. [Flickr 8k](http://nlp.cs.illinois.edu/HockenmaierGroup/Framing_Image_Description/KCCA.html)
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+10. [Flickr 30k](http://shannon.cs.illinois.edu/DenotationGraph/)
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+11. [Microsoft COCO](http://mscoco.org/home/)
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+12. [VQA](http://www.visualqa.org/)
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+13. [Image QA](http://www.cs.toronto.edu/~mren/imageqa/data/cocoqa/)
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### Frameworks
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