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15 search results found
Benchm Ml
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1,839
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
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930
A curated list of gradient boosting research papers with implementations.
Interpretable_machine_learning_with_python
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629
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
Mli Resources
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405
H2O.ai Machine Learning Interpretability Resources
Autoquant
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227
R package for automation of machine learning, forecasting, model evaluation, and model interpretation
Gbm Perf
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180
Performance of various open source GBM implementations
Benchmarks
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157
Comparison tools
Gbm Multicore
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19
GBM multicore scaling: h2o, xgboost and lightgbm on multicore and multi-socket systems
Exemplary Ml Pipeline
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14
Exemplary, annotated machine learning pipeline for any tabular data problem.
H2o Ai 101
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8
This repository covers h2o ai based implementations
Windturbineoutputprediction
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7
Work done at the H2O Open Tour NYC 2016 Hackathon, and later refinements
Python Projects
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7
Portfolio in Python
Gridisl
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6
Discrete SuperLearner with Grid-Search for Longitudinal Data
H2o Tutorial
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5
H2O Tuning and Ensembling Tutorial for R
Machine Learning Course
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5
Machine Learning and Deep Learning Course
Related Searches
Jupyter Notebook Xgboost (746)
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