Hacker News
- Calculus on Computational Graphs: Backpropagation (2015) https://colah.github.io/posts/2015-08-Backprop/ 24 comments
- Do I need to go to university? http://colah.github.io/posts/2020-05-University/ 261 comments
- Visual Information Theory (2015) https://colah.github.io/posts/2015-09-Visual-Information/ 45 comments
- Understanding Convolutions (2014) http://colah.github.io/posts/2014-07-Understanding-Convolutions/ 21 comments
- Neural Networks, Manifolds, and Topology (2014) https://colah.github.io/posts/2014-03-NN-Manifolds-Topology/ 25 comments
- Neural Networks, Types, and Functional Programming (2015) http://colah.github.io/posts/2015-09-NN-Types-FP/ 11 comments
- Understanding LSTM Networks (2015) http://colah.github.io/posts/2015-08-Understanding-LSTMs/ 10 comments
- I've decided to move on to Distill http://colah.github.io/posts/2017-03-Distill/ 46 comments
- Visual Information Theory http://colah.github.io/posts/2015-09-Visual-Information/ 21 comments
- Neural Networks, Types, and Functional Programming http://colah.github.io/posts/2015-09-NN-Types-FP/ 28 comments
- Calculus on Computational Graphs: Backpropagation http://colah.github.io/posts/2015-08-Backprop/index.html 9 comments
- Understanding LSTM networks http://colah.github.io/posts/2015-08-Understanding-LSTMs/ 17 comments
- Neural Networks, Manifolds, and Topology (2014) http://colah.github.io/posts/2014-03-NN-Manifolds-Topology/ 7 comments
- Deep Learning, NLP, and Representations http://colah.github.io/posts/2014-07-NLP-RNNs-Representations/ 9 comments
- Visualizing Representations: Deep Learning and Human Beings http://colah.github.io/posts/2015-01-Visualizing-Representations/ 15 comments
- Groups and Group Convolutions http://colah.github.io/posts/2014-12-Groups-Convolution/ 4 comments
- Visualizing MNIST: An Exploration of Dimensionality Reduction https://colah.github.io/posts/2014-10-Visualizing-MNIST/ 8 comments
- Neural Networks, Manifolds, and Topology http://colah.github.io/posts/2014-03-NN-Manifolds-Topology/ 29 comments
- Hidden Gems on Basic ML Concepts [D] https://colah.github.io/posts/2015-09-Visual-Information/ 6 comments machinelearning
- Common higher order functions on List, visualized http://colah.github.io/posts/2015-02-DataList-Illustrated/ 3 comments functionalprogramming
- Do neural networks create a separating hyperplane? https://colah.github.io/posts/2014-03-NN-Manifolds-Topology/ 2 comments learnmachinelearning
- [D] Do neural networks create a separating hyperplane? https://colah.github.io/posts/2014-03-NN-Manifolds-Topology/ 22 comments machinelearning
- A very good blog post to learn about LSTM Networks. https://colah.github.io/posts/2015-08-Understanding-LSTMs/ 22 comments learnmachinelearning
- In depth and mathematical explanation of Convolutional Neural Networks https://colah.github.io/posts/2014-07-Understanding-Convolutions/ 7 comments learnmachinelearning
- Calculus on Computational Graphs: Backpropagation (or reverse-mode differentiation). http://colah.github.io/posts/2015-08-backprop/ 14 comments math
- Questions about LSTM and PyTorch https://colah.github.io/posts/2015-08-Understanding-LSTMs/ 11 comments deeplearning
- Noob question - can I start with a "generic" first layer for a CNN? http://colah.github.io/posts/2014-07-Conv-Nets-Modular/img/KSH-filters.png 6 comments learnmachinelearning
- Understanding LSTM Networks -- colah's blog http://colah.github.io/posts/2015-08-Understanding-LSTMs/ 4 comments datascience
- If you're just learning about ML or Tensor Flow, check out: Visualizing MNIST: An Exploration of Dimensionality Reduction (Warning: Computationally Intensive Visualizations) http://colah.github.io/posts/2014-10-visualizing-mnist/ 4 comments programming
- I thought the math in this tutorial about backpropoogation was interesting. http://colah.github.io/posts/2015-08-backprop/index.html 7 comments math
- Haskell's map fold zip and their deep-neural-network equivalents RNN CNN, Colah http://colah.github.io/posts/2015-09-nn-types-fp/ 24 comments haskell
- Neural Networks, Types, and Functional Programming http://colah.github.io/posts/2015-09-nn-types-fp/ 15 comments programming
- Neural Networks, Manifolds, and Topology http://colah.github.io/posts/2014-03-nn-manifolds-topology/ 13 comments programming
- Neural Networks, Manifolds, and Topology http://colah.github.io/posts/2014-03-nn-manifolds-topology/ 22 comments math
- Neural Networks, Manifolds, and Topology. http://colah.github.io/posts/2014-03-NN-Manifolds-Topology/ 4 comments statistics
Linking pages
- High-impact research questions, by discipline - 80,000 Hours https://80000hours.org/articles/research-questions-by-discipline/ 171 comments
- My path to OpenAI https://blog.gregbrockman.com/my-path-to-openai 79 comments
- How to trick a neural network into thinking a panda is a vulture https://codewords.recurse.com/issues/five/why-do-neural-networks-think-a-panda-is-a-vulture 77 comments
- GitHub - terryum/awesome-deep-learning-papers: The most cited deep learning papers https://github.com/terryum/awesome-deep-learning-papers 47 comments
- How to Start Learning Deep Learning – Ofir Press http://ofir.io/How-to-Start-Learning-Deep-Learning/ 29 comments
- GitHub - astorfi/Deep-Learning-Roadmap: Organized Resources for Deep Learning Researchers and Developers https://github.com/astorfi/Deep-Learning-World 22 comments
- ML Resources https://sgfin.github.io/learning-resources/ 21 comments
- 100+ Best Machine Learning Blogs For Beginners https://www.theinsaneapp.com/2021/04/top-machine-learning-blogs-to-follow-in-2021.html 13 comments
- GitHub - kjw0612/awesome-rnn: Recurrent Neural Network - A curated list of resources dedicated to RNN https://github.com/kjw0612/awesome-rnn 12 comments
- GitHub - andsnw/Directory-of-Software-Eng-Resources: A curated directory of programming / software engineering resources. https://github.com/andsnw/directory-of-comp-sci-resources 8 comments
- Avi Singh's blog https://avisingh599.github.io/deeplearning/visual-qa/ 3 comments
- Nothing but NumPy: Understanding & Creating Binary Classification Neural Networks with Computational Graphs from Scratch | by Rafay Khan | Towards Data Science https://medium.com/@rafayak/nothing-but-numpy-understanding-creating-binary-classification-neural-networks-with-e746423c8d5c 2 comments
- GitHub - jkup/awesome-personal-blogs: A delightful list of personal tech blogs https://github.com/jkup/awesome-personal-blogs 1 comment
- Machine learning for artists. This spring I will be teaching a course… | by Gene Kogan | Medium https://medium.com/@genekogan/machine-learning-for-artists-e93d20fdb097#.jrbaxlwwx 1 comment
- GitHub - vlgiitr/DL_Topics: List of DL topics and resources essential for cracking interviews https://github.com/vlgiitr/DL_Topics 1 comment
- Deep-Learning-Roadmap/README.rst at master · astorfi/Deep-Learning-Roadmap · GitHub https://github.com/astorfi/Deep-Learning-World/blob/master/README.rst 0 comments
- GitHub - instillai/deep-learning-roadmap: All You Need to Know About Deep Learning - A kick-starter https://github.com/osforscience/deep-learning-comprehensive-resources 0 comments
- Recommendations for Engineers - Pawel Cislo https://pawelcislo.com/recommendations/ 0 comments
- GitHub - vyraun/Megalodon: Various ML/DL Resources organised at a single place. https://github.com/vyraun/Megalodon 0 comments
- Reduct - by Tanguy - Chatter https://thechatter.substack.com/p/reduct 0 comments