adaptive
CNTK
adaptive | CNTK | |
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11 | 1 | |
1,113 | 17,435 | |
1.4% | 0.0% | |
6.2 | 0.0 | |
6 days ago | about 1 year ago | |
Python | C++ | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
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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).
CNTK
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
Theano - Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as PyTensor: www.github.com/pymc-devs/pytensor
scikit-learn - scikit-learn: machine learning in Python
Keras - Deep Learning for humans
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
gym - A toolkit for developing and comparing reinforcement learning algorithms.
Caffe - Caffe: a fast open framework for deep learning.
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.