Linking pages
- GitHub - sindresorhus/awesome: 😎 Awesome lists about all kinds of interesting topics https://github.com/sindresorhus/awesome 69 comments
- GitHub - bayandin/awesome-awesomeness: A curated list of awesome awesomeness https://github.com/bayandin/awesome-awesomeness 66 comments
- GitHub - owainlewis/awesome-artificial-intelligence: A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers. https://github.com/owainlewis/awesome-artificial-intelligence 35 comments
- GitHub - jnv/lists: The definitive list of lists (of lists) curated on GitHub and elsewhere https://github.com/jnv/lists 28 comments
- GitHub - guillaume-chevalier/LSTM-Human-Activity-Recognition: Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier https://github.com/guillaume-chevalier/LSTM-Human-Activity-Recognition 8 comments
- What's Wrong with Scikit-Learn Pipelines? – Neuraxio https://www.neuraxio.com/en/blog/scikit-learn/2020/01/03/what-is-wrong-with-scikit-learn.html 3 comments
- GitHub - endymecy/awesome-deeplearning-resources: Deep Learning and deep reinforcement learning research papers and some codes https://github.com/endymecy/awesome-deeplearning-resources 0 comments
- Some Reasons Why Deep Learning has a Bright Future – Neuraxio https://www.neuraxio.com/en/blog/deep-learning/2019/12/29/why-deep-learning-has-a-bright-future.html 0 comments
- GitHub - guillaume-chevalier/LinkedIn-Connections-Growth-Analysis: Assessing personal growth on LinkedIn with charts. Plot LinkedIn connections over time. Discover what your connections most do and where they most work. https://github.com/guillaume-chevalier/LinkedIn-Connections-Growth-Analysis 0 comments
- GitHub - guillaume-chevalier/seq2seq-signal-prediction: Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier https://github.com/guillaume-chevalier/seq2seq-signal-prediction 0 comments
- LSTMs for Human Activity Recognition - Guillaume Chevalier's Blog https://guillaume-chevalier.com/lstms-for-human-activity-recognition/ 0 comments
- GitHub - trackawesomelist/trackawesomelist: Track 500+ Awesome List Updates, Track it - not just star it! https://github.com/trackawesomelist/trackawesomelist 0 comments
- GitHub - asetinUL/Awesome-Asetin https://github.com/asetinUL/Awesome-Asetin 0 comments
- GitHub - febinsathar/goodreads: goodreads https://github.com/febinsathar/goodreads 0 comments
- GitHub - guillaume-chevalier/Awesome-Deep-Learning-Resources: Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier https://github.com/guillaume-chevalier/favorite-deep-learning-papers 0 comments
Linked pages
- Neural networks and deep learning http://neuralnetworksanddeeplearning.com/chap4.html 520 comments
- The Unreasonable Effectiveness of Recurrent Neural Networks https://karpathy.github.io/2015/05/21/rnn-effectiveness/ 434 comments
- Creative Commons — CC0 1.0 Universal http://creativecommons.org/publicdomain/zero/1.0/ 305 comments
- https://deepmind.com/blog/wavenet-generative-model-raw-audio/ 288 comments
- How to Fold a Julia Fractal — Acko.net http://acko.net/blog/how-to-fold-a-julia-fractal/ 287 comments
- Supervised Machine Learning: Regression and Classification | Coursera https://www.coursera.org/learn/machine-learning/ 165 comments
- [1706.03762] Attention Is All You Need https://arxiv.org/abs/1706.03762 145 comments
- Neural Networks, Manifolds, and Topology -- colah's blog https://colah.github.io/posts/2014-03-NN-Manifolds-Topology/ 124 comments
- Yes you should understand backprop | by Andrej Karpathy | Medium https://medium.com/@karpathy/yes-you-should-understand-backprop-e2f06eab496b 108 comments
- [1609.08144] Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation http://arxiv.org/abs/1609.08144 97 comments
- Ray Kurzweil - Wikipedia https://en.wikipedia.org/wiki/Predictions_made_by_Ray_Kurzweil 96 comments
- Deep Learning http://www.deeplearningbook.org/ 79 comments
- Deep Learning Specialization [5 courses] (DeepLearning.AI) | Coursera https://www.coursera.org/specializations/deep-learning 73 comments
- ArticleS.UncleBob.PrinciplesOfOod http://butunclebob.com/ArticleS.UncleBob.PrinciplesOfOod 71 comments
- DataTau http://www.datatau.com 70 comments
- GitHub - sindresorhus/awesome: 😎 Awesome lists about all kinds of interesting topics https://github.com/sindresorhus/awesome 69 comments
- The future of deep learning https://blog.keras.io/the-future-of-deep-learning.html 69 comments
- arxiv-sanity http://www.arxiv-sanity.com/ 65 comments
- Neural networks and deep learning http://neuralnetworksanddeeplearning.com/chap2.html#the_four_fundamental_equations_behind_backpropagation 64 comments
- Understanding LSTM Networks -- colah's blog https://colah.github.io/posts/2015-08-Understanding-LSTMs/ 64 comments