Lobsters
- An extremely fast, Pytorch-style Tensor+Autograd library written in Rust https://github.com/bkkaggle/L2 3 comments ai , rust
Linked pages
- GitHub - amitmerchant1990/electron-markdownify: A minimal Markdown editor desktop app https://github.com/amitmerchant1990/electron-markdownify 169 comments
- http://course.fast.ai/part2.html 115 comments
- Yes you should understand backprop | by Andrej Karpathy | Medium https://medium.com/@karpathy/yes-you-should-understand-backprop-e2f06eab496b 108 comments
- GitHub - athityakumar/colorls: A Ruby gem that beautifies the terminal's ls command, with color and font-awesome icons. :tada: https://github.com/athityakumar/colorls 103 comments
- GitHub - mratsim/Arraymancer: A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends https://github.com/mratsim/arraymancer 41 comments
- Things Rust doesn’t let you do. A survey of things that Rust doesn’t… | by Pyry Kontio | Medium https://medium.com/@golddranks/things-rust-doesnt-let-you-do-draft-f596a3c740a5 26 comments
- The MIT License | Open Source Initiative https://opensource.org/licenses/MIT 15 comments
- GitHub - rish-16/gpt2client: ✍🏻 gpt2-client: Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, and 1.5B Transformer Models 🤖 📝 https://github.com/rish-16/gpt2client 10 comments
- PyTorch internals : ezyang’s blog http://blog.ezyang.com/2019/05/pytorch-internals/ 10 comments
- Building an autodifferentiation library | by Maciej Kula | Medium https://medium.com/@maciejkula/building-an-autodifferentiation-library-9ccf32c7a658 10 comments
- How To Create A Machine Learning Framework From Scratch In 491 steps | by Florian Cäsar | Medium https://medium.com/@florian.caesar/how-to-create-a-machine-learning-framework-from-scratch-in-491-steps-93428369a4eb 4 comments
- GitHub - xtensor-stack/xtensor: C++ tensors with broadcasting and lazy computing https://github.com/QuantStack/xtensor 2 comments
- GitHub - Daniel-Liu-c0deb0t/Java-Machine-Learning: Deep learning library for Java, with fully connected, convolutional, and recurrent layers. Also features many gradient descent optimization algorithms. https://github.com/Daniel-Liu-c0deb0t/Java-Machine-Learning 1 comment
- GitHub - karpathy/micrograd: A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API https://github.com/karpathy/micrograd 0 comments
- GitHub - explosion/thinc: 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries https://github.com/explosion/thinc 0 comments
- Reverse-mode automatic differentiation: a tutorial - Rufflewind's Scratchpad https://rufflewind.com/2016-12-30/reverse-mode-automatic-differentiation 0 comments
- CS231n Convolutional Neural Networks for Visual Recognition https://cs231n.github.io/optimization-2/ 0 comments
- What is torch.nn really? — PyTorch Tutorials 1.13.1+cu117 documentation https://pytorch.org/tutorials/beginner/nn_tutorial.html 0 comments
- Rust for Machine Learning: SIMD, BLAS, and Lapack - Erik Partridge https://www.erikpartridge.com/2019-03/rust-ml-simd-blas-lapack 0 comments
- PyTorch Basics: Understanding Autograd and Computation Graphs https://blog.paperspace.com/pytorch-101-understanding-graphs-and-automatic-differentiation/ 0 comments
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