deep-active-learning
adaptive
| deep-active-learning | adaptive | |
|---|---|---|
| 1 | 11 | |
| 758 | 1,114 | |
| - | 1.5% | |
| 10.0 | 6.2 | |
| over 1 year ago | 7 days ago | |
| Python | Python | |
| MIT License | BSD 3-clause "New" or "Revised" License |
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deep-active-learning
adaptive
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I made a Python package to do adaptive learning of functions in parallel [P]
Imagine you have a drawing with lots of hills and valleys, and you want to understand the shape of the landscape. Instead of measuring the height at every single point, Adaptive helps you measure the height at the most important points. It focuses on areas where the hills and valleys change a lot, so you can understand the drawing with fewer measurements.
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I made a Python package to do adaptive sampling of functions in parallel [OC]
Yes! Check it out at https://github.com/python-adaptive/adaptive/
Explore and star ⭐️ the repo on github.com/python-adaptive/adaptive, and check out the documentation at adaptive.readthedocs.io.
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Also, Quatro will require a YAML annotation at the top of the file that will always be visible, e.g., a notebook on GitHub: https://github.com/python-adaptive/adaptive/blob/main/docs/source/tutorial/tutorial.DataSaver.md
- Does Julia have something like pythons adaptive?
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Graph plotting software for nasty function
Getting Python to calculate the equation for you shouldn't be a problem. The problem is that it may be having trouble figuring out which points to sample from. Using a uniformly spaced set of points won't necessarily result in the best looking curve, especially after interpolation. There is the adaptive package which does smart sampling of expensive functions. The idea is you give the function, and the adaptive library will learn the best x values to use and also return f(x).
What are some alternatives?
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cleanlab - The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
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modAL - A modular active learning framework for Python
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