xorbits
Scalable Python DS & ML, in an API compatible & lightning fast way. (by xorbitsai)
adaptive
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions (by python-adaptive)
| xorbits | adaptive | |
|---|---|---|
| 7 | 11 | |
| 1,011 | 1,113 | |
| 1.7% | 1.4% | |
| 8.8 | 6.2 | |
| about 1 month ago | 4 days ago | |
| Python | Python | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
xorbits
Posts with mentions or reviews of xorbits.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-03.
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Everything you need to know about pandas 2.0.0!
Here’s our project: https://github.com/xprobe-inc/xorbits
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Introducing Xorbits: A Distributed Python Data Science Framework for Large Dataset Analysis
Hey everyone, we are excited to announce our new project, Xorbits, a scalable data science framework that aims to scale the entire Python data science world.
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Use maximum PC Hardware Resources
My suggestion is to use some parallel computing framework like Xorbits. The framework will parallel your workload automatically. For data processing tasks, just use xorbits.pandas or xorbits.numpy, and you can run almost any python workload with xorbits.remote.
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Use "distributed pandas" to scale your data science workflow!
If you are interested in learning more about Xorbits, please visit our project's Github for more information: https://github.com/xprobe-inc/xorbits
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A new way to accelerate your data science workflow
Xorbits can be an ideal solution for these issues. Xorbits is a scalable Python data science framework that aims to scale the Python data science stack while keeping the API compatibility. You can get an out-of-box performance gain by changing `import pandas as pd` to `import xorbits.pandas as pd`.
- Scalable Python data science, in an API compatible and fast way
adaptive
Posts with mentions or reviews of adaptive.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-29.
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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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Introducing Markdown Code Runner: Automatically execute code blocks in your Markdown files! 🚀
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?
When comparing xorbits and adaptive you can also consider the following projects:
Data Flow Facilitator for Machine Learning (dffml) - The easiest way to use Machine Learning. Mix and match underlying ML libraries and data set sources. Generate new datasets or modify existing ones with ease.
tensorflow - An Open Source Machine Learning Framework for Everyone
scikit-learn - scikit-learn: machine learning in Python
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Keras - Deep Learning for humans
seqeval - A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)
gym - A toolkit for developing and comparing reinforcement learning algorithms.
PyBrain
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
trueskill - An implementation of the TrueSkill rating system for Python