Hacker News
- A curated list of resources dedicated to recurrent neural networks https://github.com/kjw0612/awesome-rnn 12 comments
Linking pages
- GitHub - bayandin/awesome-awesomeness: A curated list of awesome awesomeness https://github.com/bayandin/awesome-awesomeness 66 comments
- GitHub - terryum/awesome-deep-learning-papers: The most cited deep learning papers https://github.com/terryum/awesome-deep-learning-papers 47 comments
- GitHub - jnv/lists: The definitive list of lists (of lists) curated on GitHub and elsewhere https://github.com/jnv/lists 28 comments
- Machine Learning is Fun Part 5: Language Translation with Deep Learning and the Magic of Sequences | by Adam Geitgey | Medium https://medium.com/@ageitgey/machine-learning-is-fun-part-5-language-translation-with-deep-learning-and-the-magic-of-sequences-2ace0acca0aa 1 comment
- GitHub - cuuupid/awesome-lists: A curated list of curated lists. https://github.com/cuuupid/awesome-lists 1 comment
- An Introduction to Deep Learning for Generative Models http://www.ymer.org/amir/2016/11/21/an-introduction-to-deep-learning-for-generative-models/ 0 comments
- A short guide to learn neural networks, and get famous and rich then. | by Sergey Enin | Chatbots Life https://chatbotslife.com/a-short-guide-to-learn-neural-networks-and-get-famous-and-rich-then-bf7da3cba76f#.xytus7haq 0 comments
- GitHub - robertsdionne/neural-network-papers https://github.com/robertsdionne/neural-network-papers 0 comments
- GitHub - mbadry1/Top-Deep-Learning: Top 200 deep learning Github repositories sorted by the number of stars. https://github.com/mbadry1/Top-Deep-Learning 0 comments
- Babies are awesome… Humans are the OG neural net. | by Jingles (Hong Jing) | Towards Data Science https://towardsdatascience.com/babies-are-awesome-humans-are-the-og-neural-net-e2dc83fe9eff?sk=50c7e910197c4a368f3bfa14513d2d07&source=friends_link 0 comments
- GitHub - ujjwalkarn/Machine-Learning-Tutorials: machine learning and deep learning tutorials, articles and other resources https://github.com/ujjwalkarn/Machine-Learning-Tutorials 0 comments
- GitHub - aikorea/awesome-rl: Reinforcement learning resources curated https://github.com/aikorea/awesome-rl 0 comments
Linked pages
- TensorFlow http://tensorflow.org/ 440 comments
- The Unreasonable Effectiveness of Recurrent Neural Networks https://karpathy.github.io/2015/05/21/rnn-effectiveness/ 434 comments
- GitHub - karpathy/neuraltalk: NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences. https://github.com/karpathy/neuraltalk 143 comments
- PyTorch http://pytorch.org/ 100 comments
- http://www.cs.toronto.edu/~graves/handwriting.html 80 comments
- Understanding LSTM Networks -- colah's blog https://colah.github.io/posts/2015-08-Understanding-LSTMs/ 64 comments
- GitHub - aymericdamien/TensorFlow-Examples: TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2) https://github.com/aymericdamien/TensorFlow-Examples 50 comments
- Keras: the Python deep learning API https://keras.io 46 comments
- http://arxiv.org/abs/1410.5401 40 comments
- Deep Visual-Semantic Alignments for Generating Image Descriptions http://cs.stanford.edu/people/karpathy/deepimagesent/ 39 comments
- CS231n Convolutional Neural Networks for Visual Recognition https://cs231n.github.io 30 comments
- GitHub - karpathy/neuraltalk2: Efficient Image Captioning code in Torch, runs on GPU https://github.com/karpathy/neuraltalk2 23 comments
- GitHub - IDSIA/brainstorm: Fast, flexible and fun neural networks. https://github.com/IDSIA/brainstorm 18 comments
- Machine Learning https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/ 18 comments
- http://deeplearning.cs.toronto.edu/i2t 17 comments
- https://dennybritz.com/posts/wildml/rnns-in-tensorflow-a-practical-guide-and-undocumented-features/ http://www.wildml.com/2016/08/rnns-in-tensorflow-a-practical-guide-and-undocumented-features/ 13 comments
- http://www.deeplearning.net/software/theano/ 12 comments
- http://deeplearning4j.org/lstm.html 10 comments
- Torch | Scientific computing for LuaJIT. http://torch.ch/ 9 comments
- http://arxiv.org/pdf/1502.04623.pdf 7 comments
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