Based on our record, nuitka seems to be a lot more popular than Scale Nucleus. While we know about 37 links to nuitka, we've tracked only 2 mentions of Scale Nucleus. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Nuitka is actively maintained and support for 2.6 and 2.7. It is the work of a single guy, and I have never used it, so I don't know much about it. https://nuitka.net/. - Source: Hacker News / 23 days ago
This is a good place to mention https://nuitka.net/ which aims to compile python programs into standalone binaries. - Source: Hacker News / 2 months ago
For Python, you could make a proper deployment binary using Nuitka (in standalone mode – avoid onefile mode for this). I'm not pretending it's as easy as building a Go executable: you may have to do some manual hacking for more unusual unusual packages, and I don't think you can cross compile. I think a key element you're getting at is that Go executables have very few dependencies on OS packages, but with Python... - Source: Hacker News / 3 months ago
There is already an AOT compiler for Python: Nuitka[0]. But I don't think it's much faster. And then there is mypyc[1] which uses mypy's static type annotations but is only slightly faster. And various other compilers like Numba and Cython that work with specialized dialects of Python to achieve better results, but then it's not quite Python anymore. [0] https://nuitka.net/ [1] - Source: Hacker News / 5 months ago
Nuitka deals pretty well with those in general: https://nuitka.net/. - Source: Hacker News / 11 months ago
At Scale we built a tool for model debugging in computer vision called Nucleus (scale.com/nucleus) designed exactly for this, which is free try out if you're curious to see where your model predictions are most at odds with your ground truth. Source: over 2 years ago
To address your point about gathering edge cases, which can also be defined as cases of low model fidelity for our use cases, there is active learning and tools such as Aquarium Learning and Scale Nucleus which make it easy to implement into workflows. Source: almost 3 years ago
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