Linking pages
- JAX Quickstart — JAX documentation https://jax.readthedocs.io/en/latest/notebooks/quickstart.html 143 comments
- GitHub - google/jax: Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more https://github.com/google/jax 99 comments
- Eager Execution: An imperative, define-by-run interface to TensorFlow – Google AI Blog https://research.googleblog.com/2017/10/eager-execution-imperative-define-by.html 35 comments
- A Purely Functional Typed Approach to Trainable Models (Part 1) · in Code https://blog.jle.im/entry/purely-functional-typed-models-1.html 32 comments
- GitHub - breandan/kotlingrad: 🧩 Shape-Safe Symbolic Differentiation with Algebraic Data Types https://github.com/breandan/kotlingrad 27 comments
- A new trick for calculating Jacobian vector products https://j-towns.github.io/2017/06/12/A-new-trick.html 14 comments
- GitHub - mikeroyal/Neuromorphic-Computing-Guide: Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures. https://github.com/mikeroyal/Neuromorphic-Computing-Guide 7 comments
- GitHub - mstksg/backprop: Heterogeneous automatic differentiation ("backpropagation") in Haskell https://github.com/mstksg/backprop 7 comments
- Introducing our Hybrid lda2vec Algorithm | Stitch Fix Technology â Multithreaded http://multithreaded.stitchfix.com/blog/2016/05/27/lda2vec/ 4 comments
- The Policy of Truth – arg min blog http://www.argmin.net/2018/02/20/reinforce/ 4 comments
- Run Your Own DALL·E Mini (Craiyon) Server on EC2 | by Meadowrun | Medium https://medium.com/@meadowrun/run-your-own-dall-e-mini-craiyon-server-on-ec2-e8aef6f974c1 2 comments
- GitHub - daturkel/learning-papers: Landmark Papers in Machine Learning https://github.com/daturkel/learning-papers 1 comment
- Optimizing a Wing Inside a Fluid Simulation https://greydanus.github.io/2020/10/14/optimizing-a-wing/ 1 comment
- GitHub - 1duo/awesome-ai-infrastructures: Infrastructures™ for Machine Learning Training/Inference in Production. https://github.com/1duo/awesome-ai-infrastructures 1 comment
- GitHub - pytorch/pytorch: Tensors and Dynamic neural networks in Python with strong GPU acceleration https://github.com/pytorch/pytorch 1 comment
- JAX: High-Performance Array Computing — JAX documentation https://jax.readthedocs.io/ 1 comment
- GitHub - amrzv/awesome-colab-notebooks: Collection of google colaboratory notebooks for fast and easy experiments https://github.com/amrzv/awesome-colab-notebooks 0 comments
- PyTorch and TensorFlow: Which ML Framework is More Popular in Academia and Industry https://www.infoq.com/news/2019/11/State-Machine-Learning-fw-2019/ 0 comments
- The Next Generation of Machine Learning Tools | Roman Ring http://inoryy.com/post/next-gen-ml-tools/ 0 comments
- GitHub - r0f1/datascience: Curated list of Python resources for data science. https://github.com/r0f1/datascience 0 comments
Linked pages
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