openskill.py
LightFM
Our great sponsors
| openskill.py | LightFM | |
|---|---|---|
| 22 | - | |
| 241 | 4,600 | |
| 4.1% | 0.9% | |
| 7.3 | 4.8 | |
| 6 days ago | 4 months ago | |
| Jupyter Notebook | Python | |
| MIT License | Apache License 2.0 |
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.
openskill.py
- Show HN: Predict team ranks in sports and video games with openskill.py
- Predict how teams will rank in sports/video games using our rating system.
- I made a project with the ability to predict ranks of teams in a sports/video game match.
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Openskill: A patent-free alternative to TrueSkill
Linked is the Javascript library. There are also ports of this to Python, Kotlin, Lua, and Elixir.
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Predicting Overwatch Match Outcomes with 90% Accuracy
The new benchmark code can be found here.
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openskill.py VS trueskill - a user suggested alternative
2 projects | 30 Jan 2022
- openskill.py can now predict the winners of any game with 90% accuracy and faster than TrueSkill
LightFM
We haven't tracked posts mentioning LightFM yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
trueskill - An implementation of the TrueSkill rating system for Python
Surprise - A Python scikit for building and analyzing recommender systems
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
tensorflow - An Open Source Machine Learning Framework for Everyone
karateclub - Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
implicit - Fast Python Collaborative Filtering for Implicit Feedback Datasets
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.
MLflow - Open source platform for the machine learning lifecycle
seqeval - A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)
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
spotlight - Deep recommender models using PyTorch.