Hacker News
- The Unreasonable Effectiveness of Recurrent Neural Networks (2015) http://karpathy.github.io/2015/05/21/rnn-effectiveness/ 51 comments
- The Unreasonable Effectiveness of Recurrent Neural Networks (2015) https://karpathy.github.io/2015/05/21/rnn-effectiveness/ 6 comments
- The Unreasonable Effectiveness of Recurrent Neural Networks http://karpathy.github.io/2015/05/21/rnn-effectiveness/ 207 comments
Lobsters
- The Unreasonable Effectiveness of Recurrent Neural Networks http://karpathy.github.io/2015/05/21/rnn-effectiveness/ 4 comments programming
- [P] Generative Language Model (GRU) learns constant representation http://karpathy.github.io/2015/05/21/rnn-effectiveness/ 2 comments machinelearning
- [D] Character-level vs. word-level tokenization http://karpathy.github.io/2015/05/21/rnn-effectiveness/ 15 comments machinelearning
- mltype - Typing practice for Elixir and other languages http://karpathy.github.io/2015/05/21/rnn-effectiveness/ 3 comments elixir
- mltype - Typing practice for programming languages http://karpathy.github.io/2015/05/21/rnn-effectiveness/ 13 comments opensource
- Which part of the RNN architecture has the sequential memory stored ? http://karpathy.github.io/2015/05/21/rnn-effectiveness/ 7 comments learnmachinelearning
- Best ML approach to this problem? http://karpathy.github.io/2015/05/21/rnn-effectiveness/ 5 comments learnmachinelearning
- New to AI, where to start? http://karpathy.github.io/2015/05/21/rnn-effectiveness/ 5 comments artificial
- The Unreasonable Effectiveness of Recurrent Neural Networks https://karpathy.github.io/2015/05/21/rnn-effectiveness/ 8 comments programming
- The Unreasonable Effectiveness of Recurrent Neural Networks http://karpathy.github.io/2015/05/21/rnn-effectiveness/ 106 comments programming
Linking pages
- All Roads Lead to Rome: The Machine Learning Job Market in 2022 | Eric Jang https://evjang.com/2022/04/25/rome.html 259 comments
- How you can train an AI to convert your design mockups into HTML and CSS https://medium.freecodecamp.org/how-you-can-train-an-ai-to-convert-your-design-mockups-into-html-and-css-cc7afd82fed4 155 comments
- GitHub - minimaxir/textgenrnn: Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code. https://github.com/minimaxir/textgenrnn 154 comments
- Composing Music With Recurrent Neural Networks · Daniel D. Johnson http://www.hexahedria.com/2015/08/03/composing-music-with-recurrent-neural-networks/ 132 comments
- GitHub - brexhq/prompt-engineering: Tips and tricks for working with Large Language Models like OpenAI's GPT-4. https://github.com/brexhq/prompt-engineering 105 comments
- How to Get a Job in Deep Learning - Deepgram Blog ⚡️ http://blog.deepgram.com/how-to-get-a-job-in-deep-learning/ 86 comments
- My path to OpenAI https://blog.gregbrockman.com/my-path-to-openai 79 comments
- visakanv-RNN — machine-generated husband chatter | by Sharan Kaur | HackerNoon.com | Medium https://medium.com/@sharanvkaur/visakanv-rnn-machine-generated-husband-chatter-c2b431bf0ac2 68 comments
- GitHub - HuwCampbell/grenade: Deep Learning in Haskell https://github.com/HuwCampbell/grenade 68 comments
- GitHub - oxford-cs-deepnlp-2017/lectures: Oxford Deep NLP 2017 course https://github.com/oxford-cs-deepnlp-2017/lectures 66 comments
- RWKV: Reinventing RNNs for the Transformer Era — with Eugene Cheah of UIlicious https://www.latent.space/p/rwkv#%C2%A7the-eleuther-mafia 66 comments
- Generative Models https://openai.com/blog/generative-models/ 60 comments
- Exploring LSTMs http://blog.echen.me/2017/05/30/exploring-lstms/ 59 comments
- machine-learning-experiments/recipes_generation.en.md at master · trekhleb/machine-learning-experiments · GitHub https://github.com/trekhleb/machine-learning-experiments/blob/master/assets/recipes_generation.en.md 51 comments
- Recurrent Net Dreams Up Fake Chinese Characters in Vector Format with TensorFlow | 大トロ http://blog.otoro.net/2015/12/28/recurrent-net-dreams-up-fake-chinese-characters-in-vector-format-with-tensorflow/ 48 comments
- Transformers from scratch | peterbloem.nl http://peterbloem.nl/blog/transformers 40 comments
- Playing Mortal Kombat with TensorFlow.js. Transfer learning and data augmentation · Minko Gechev's blog https://blog.mgechev.com/2018/10/20/transfer-learning-tensorflow-js-data-augmentation-mobile-net/ 34 comments
- An Adversarial Review of “Adversarial Generation of Natural Language” | by Yoav Goldberg | Medium https://medium.com/@yoav.goldberg/an-adversarial-review-of-adversarial-generation-of-natural-language-409ac3378bd7 34 comments
- The Unreasonable Syntactic Expressivity of RNNs · John Hewitt https://nlp.stanford.edu/~johnhew/rnns-hierarchy.html 34 comments
- Training a Recurrent Neural Network to Compose Music https://maraoz.com/2016/02/02/abc-rnn/ 32 comments
Linked pages
- 500'000€ Prize for Compressing Human Knowledge http://prize.hutter1.net/ 253 comments
- GitHub - torvalds/linux: Linux kernel source tree https://github.com/torvalds/linux 228 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
- http://www.cs.toronto.edu/~graves/handwriting.html 80 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
- Jupyter Notebook Viewer http://nbviewer.ipython.org/gist/yoavg/d76121dfde2618422139 38 comments
- http://cs.stanford.edu/people/jcjohns/fake-math/4.pdf 34 comments
- GitHub - keras-team/keras: Deep Learning for humans https://github.com/fchollet/keras/ 32 comments
- Essays http://paulgraham.com/articles.html 12 comments
- Torch | Scientific computing for LuaJIT. http://torch.ch/ 9 comments
- Index—The Stacks project http://stacks.math.columbia.edu/ 1 comment
- [1505.02074] Exploring Models and Data for Image Question Answering http://arxiv.org/abs/1505.02074 0 comments
- http://cs.stanford.edu/people/karpathy/namesGenUnique.txt 0 comments
- GitHub - karpathy/char-rnn: Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch https://github.com/karpathy/char-rnn 0 comments
- Obama-RNN — Machine generated political speeches. | by samim | Medium https://medium.com/@samim/obama-rnn-machine-generated-political-speeches-c8abd18a2ea0 0 comments
- [1406.6247] Recurrent Models of Visual Attention http://arxiv.org/abs/1406.6247 0 comments
- [1505.00521] Reinforcement Learning Neural Turing Machines - Revised http://arxiv.org/abs/1505.00521 0 comments
- Visualizing and Understanding Recurrent Networks | SkillsCast | 10th September 2015 https://skillsmatter.com/skillscasts/6611-visualizing-and-understanding-recurrent-networks 0 comments
- DeepMind https://www.deepmind.com 0 comments
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