Next Meetup

[One week hack] Discuss classic deep learning articles and coding
Tones of DL are there, but here are the fundamental ideas. Come and discuss them: A Few Useful Things to Know about Machine Learning (http://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf) by Pedro Domingos Deep Learning (https://www.cs.toronto.edu/~hinton/absps/NatureDeepReview.pdf) by Yann LeCun, Yoshua Bengio, and Geoffrey Hinton Representation Learning: A Review and New Perspectives (http://www.cl.uni-heidelberg.de/courses/ws14/deepl/BengioETAL12.pdf) by Yoshua Bengio, Aaron Courville, Pascal Vincent Convolutional Networks for Images, Speech and Time-Series (http://yann.lecun.com/exdb/publis/pdf/lecun-bengio-95a.pdf) by Yann LeCun and Yoshua Bengio Learning Deep Architectures for AI (https://www.iro.umontreal.ca/~lisa/pointeurs/TR1312.pdf) by Yoshua Bengio ImageNet Classification with Deep Convolutional Neural Networks (https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf) by Alex Krizhevsky, Ilya Sutskever and Geoffery Hinton LSTM: A Search Space Odyssey (http://arxiv.org/pdf/1503.04069.pdf) by Klaus Greff, Rupesh K. Srivastava, Jan Koutník, Bas R. Steunebrink and Jürgen Schmidhuber Distributed Representations of Words and Phrases and Their Compositionality (https://arxiv.org/pdf/1310.4546.pdf) by Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado and Jeffrey Dean Recurrent Neural Network Based Language Model (http://www.fit.vutbr.cz/research/groups/speech/publi/2010/mikolov_interspeech2010_IS100722.pdf) by Tomas Mikolov, Martin Karafiat, Lukas Burget, Jan Cernocky, Sanjeev Khudanpur Sequence to Sequence Learning with Neural Networks (http://arxiv.org/pdf/1409.3215v3.pdf) by Ilya Sutskever, Oriol Vinyals and Quoc V. Le Text Understanding from Scratch (https://arxiv.org/pdf/1502.01710.pdf) by Xiang Zhang and Yann LeCun

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