ml.js
shumai
| ml.js | shumai | |
|---|---|---|
| 2 | 15 | |
| 2,503 | 1,122 | |
| 1.0% | 0.2% | |
| 4.7 | 2.2 | |
| 3 months ago | 10 months ago | |
| JavaScript | TypeScript | |
| MIT License | MIT License |
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ml.js
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Why do people curse JS so much, but also say it's better than Python
ML.js: This is a library for machine learning in JavaScript. It provides a wide range of algorithms including linear regression, k-means, and decision trees, as well as utility functions for data pre-processing and model evaluation.
- Data Science And Machine Learning In JavaScript
shumai
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PyTorch Primitives in WebGPU for the Browser
https://github.com/tensorflow/tfjs/tree/master/tfjs-backend-...
([...], tflite-support, tflite-micro)
From facebookresearch/shumai (a JS tensor library) https://github.com/facebookresearch/shumai/issues/122 :
> It doesn't make sense to support anything besides WebGPU at this point. WASM + SIMD is around 15-20x slower on my machine[1]. Although WebGL is more widely supported today, it doesn't have the compute features needed for efficient modern ML (transformers etc) and will likely be a deprecated backend for other frameworks when WebGPU comes online.
tensorflow rust has a struct.Tensor:
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Why do people curse JS so much, but also say it's better than Python
JS for ML actually does exist https://github.com/facebookresearch/shumai
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Breaking Up with Python
> It's really a shame that data science, ML, and notebooks are so wrapped up in it. Otherwise we could jettison the whole thing into space
Although I personally feel Python has its place, I contribute to a project that hopes to diversify the ML/scientific computing space with a TypeScript tensor lib called Shumai: https://github.com/facebookresearch/shumai
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Tinygrad: A simple and powerful neural network framework
Doesn’t really matter for large batch/large model training on GPUs that don’t need much coordination.
But Python speed is one of the main motivations for a JS/TS based ML lib I’m working on: https://github.com/facebookresearch/shumai
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[D] Using JavaScript for ML Training/Research (not in the browser)
As a hedge against CPython never becoming fast, we're creating a project called Shumai that attempts to deeply integrate with a new JavaScript runtime (Bun[3]).
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Python 3.11 is much faster than 3.8
You can expose objects. Here's how it is done in Bun: https://github.com/facebookresearch/shumai/blob/main/shumai/...
We've been using this feature heavily in Shumai.
I think you are vastly overestimating the complexity associated with this (user exposed ref-counting/garbage collection) and may not be totally up to date on what's implemented.
- Shumai: Fast Differentiable Tensor Library in TypeScript with Bun and Flashlight
- Shumai: A fast differentiable tensor library for research in TypeScript and JavaScript
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7% Speedup from Switch to and
This thought is pretty much the exact motivation behind a recent effort I’m helping out with https://github.com/facebookresearch/shumai
What are some alternatives?
Brain.js - Simple feed-forward neural network in JavaScript
rosettaboy - A gameboy emulator in several different languages
neurojs - A JavaScript deep learning and reinforcement learning library.
jittor - Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
limdu - Machine-learning for Node.js
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
DN2A - Dynamic Neural Networks Architect
devdocs - API Documentation Browser
Synapses - A group of neural-network libraries for functional and mainstream languages
FrameworkBenchmarks - Source for the TechEmpower Framework Benchmarks project
ConvNetJS - Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration