xorbits
trueskill
| xorbits | trueskill | |
|---|---|---|
| 7 | 1 | |
| 1,011 | 735 | |
| 1.7% | - | |
| 8.8 | 1.4 | |
| about 1 month ago | 8 months ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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
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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
trueskill
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openskill.py VS trueskill - a user suggested alternative
2 projects | 30 Jan 2022
Trueskill is used to predict winners of a game just like openskill.
What are some alternatives?
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.
openskill.py - Multiplayer Rating System. No Friction.
tensorflow - An Open Source Machine Learning Framework for Everyone
pyro - Deep universal probabilistic programming with Python and PyTorch
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
seqeval - A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)
Surprise - A Python scikit for building and analyzing recommender systems
PyBrain
H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.