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h2oai / h2o-3

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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.

python java data-science machine-learning multi-threading opensource r big-data spark deep-learning hadoop random-forest gpu naive-bayes h2o distributed pca gbm ensemble-learning automl
  • Updated Dec 30, 2020
  • Jupyter Notebook

rapidsai / cudf

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[FEA] logical_cast from FLOAT32 to INT32 and FLOAT64 to INT64 or bit_cast for the same

revans2
revans2 commented Nov 23, 2020

Spark is really inconsistent in how it handles some values like -0.0 vs 0.0 and the various NaN values that are possible. I don't expect cuDF to be aware of any of this, but I would like the ability to work around it in some cases by treating the floating point value as if it were just a bunch of bits. To me logical_cast feels like the right place to do this, but floating point values are

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Spark cuDF (Java) feature request good first issue
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awesome-gradient-boosting-papers

benedekrozemberczki / awesome-gradient-boosting-papers

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A curated list of gradient boosting research papers with implementations.

classifier machine-learning deep-learning random-forest h2o xgboost lightgbm gradient-boosting-machine adaboost decision-tree gradient-boosting-classifier classification-algorithm gradient-boosting boosting classification-trees xgboost-algorithm catboost gradient-boosted-trees classification-tree gradient-boosting-decision-trees
  • Updated Dec 21, 2020
  • Python

kaiwaehner / kafka-streams-machine-learning-examples

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This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.

python java open-source machine-learning kafka deep-learning tensorflow h2o keras kafka-client kafka-streams dl4j keras-tensorflow h2oai deeplearning4j ksql
  • Updated Nov 26, 2020
  • Java

jphall663 / interpretable_machine_learning_with_python

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Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

python data-science machine-learning data-mining h2o gradient-boosting-machine transparency decision-tree fairness lime accountability interpretability interpretable-ai interpretable-ml xai fatml interpretable interpretable-machine-learning iml machine-learning-interpretability
  • Updated Oct 1, 2020
  • Jupyter Notebook
RemixAutoML

AdrianAntico / RemixAutoML

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R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.

machine-learning r timeseries transformations h2o regression supervised-learning xgboost classification gpu-acceleration recommender-system feature-engineering unsupervised-learning multiclass-classification automated-machine-learning anomaly-detection market-basket-analysis catboost nonlinear-regression cost-sensitive-classification
  • Updated Dec 29, 2020
  • R

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