Windturbineoutputprediction
Work done at the H2O Open Tour NYC 2016 Hackathon, and later refinements
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Benchm Ml | 1,839 | 2 years ago | 11 | mit | R | |||||
| A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.). | ||||||||||
| Awesome Gradient Boosting Papers | 930 | 10 months ago | 1 | cc0-1.0 | Python | |||||
| A curated list of gradient boosting research papers with implementations. | ||||||||||
| Interpretable_machine_learning_with_python | 629 | a year ago | 1 | Jupyter Notebook | ||||||
| Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security. | ||||||||||
| Mli Resources | 405 | 3 years ago | 4 | Jupyter Notebook | ||||||
| H2O.ai Machine Learning Interpretability Resources | ||||||||||
| Autoquant | 227 | 4 months ago | agpl-3.0 | R | ||||||
| R package for automation of machine learning, forecasting, model evaluation, and model interpretation | ||||||||||
| Gbm Perf | 180 | 3 years ago | 30 | mit | HTML | |||||
| Performance of various open source GBM implementations | ||||||||||
| Benchmarks | 157 | 9 months ago | 5 | apache-2.0 | Jupyter Notebook | |||||
| Comparison tools | ||||||||||
| Gbm Multicore | 19 | 6 years ago | 2 | HTML | ||||||
| GBM multicore scaling: h2o, xgboost and lightgbm on multicore and multi-socket systems | ||||||||||
| Exemplary Ml Pipeline | 14 | 5 years ago | mit | Jupyter Notebook | ||||||
| Exemplary, annotated machine learning pipeline for any tabular data problem. | ||||||||||
| H2o Ai 101 | 8 | 5 years ago | mit | Jupyter Notebook | ||||||
| This repository covers h2o ai based implementations | ||||||||||
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