Hacker News
- Backpropagation is a leaky abstraction https://medium.com/@karpathy/yes-you-should-understand-backprop-e2f06eab496b#.lbzzq2acs 101 comments
- Question regarding eigenvectors in Andrej Karpathy's post on Medium. https://medium.com/@karpathy/yes-you-should-understand-backprop-e2f06eab496b 7 comments learnmachinelearning
Linking pages
- AI Canon | Andreessen Horowitz https://a16z.com/2023/05/25/ai-canon/ 219 comments
- A Recipe for Training Neural Networks http://karpathy.github.io/2019/04/25/recipe/#2-set-up-the-end-to-end-trainingevaluation-skeleton--get-dumb-baselines 39 comments
- Learning Deep Learning with Keras http://p.migdal.pl/2017/04/30/teaching-deep-learning.html 5 comments
- GitHub - bilal2vec/L2: l2 is a fast, Pytorch-style Tensor+Autograd library written in Rust https://github.com/bkkaggle/L2 4 comments
- Troubleshooting Convolutional Neural Nets · GitHub https://gist.github.com/zeyademam/0f60821a0d36ea44eef496633b4430fc 3 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/awesome-deep-learning-resources 1 comment
- Thoughts after taking the Deeplearning.ai courses | by Arvind N | Towards Data Science https://medium.com/@gedanken.thesis/thoughts-after-taking-the-deeplearning-ai-courses-8568f132153 1 comment
- Saliency Maps for Deep Learning: Vanilla Gradient | by Andrew Schreiber | Medium https://medium.com/@thelastalias/saliency-maps-for-deep-learning-part-1-vanilla-gradient-1d0665de3284 0 comments
- Identifying Traffic Signs with Deep Learning | by Harshit Sharma | Towards Data Science https://medium.com/towards-data-science/identifying-traffic-signs-with-deep-learning-5151eece09cb 0 comments
- How to train your Deep Neural Network – Rishabh Shukla http://rishy.github.io/ml/2017/01/05/how-to-train-your-dnn/ 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
- CS231n Convolutional Neural Networks for Visual Recognition https://cs231n.github.io 30 comments
- Leaky abstraction - Wikipedia https://en.wikipedia.org/wiki/Leaky_abstraction#The_Law_of_Leaky_Abstractions 4 comments
- Understanding the backward pass through Batch Normalization Layer https://kratzert.github.io/2016/02/12/understanding-the-gradient-flow-through-the-batch-normalization-layer.html 0 comments
- CS231n Winter 2016: Lecture 4: Backpropagation, Neural Networks 1 - YouTube https://youtu.be/i94OvYb6noo 0 comments
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