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h2oai / h2o-3

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Open Source Fast Scalable Machine Learning Platform For Smarter Applications: Deep Learning, Gradient Boosting & XGBoost, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, 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 Nov 13, 2020
  • Jupyter Notebook

rapidsai / cudf

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Open

[BUG] CSV writer parameter rows_per_chunk has a bad default value

vuule
vuule commented Nov 4, 2020

Current default value for rows_per_chunk parameter of the CSV writer is 8, which means that the input table is by default broken into many small slices that are written out sequentially. This reduces the performance by an order on magnitude in some cases.

In Python layer, the default is the number of rows (i.e. write table out in a single pass). We can follow this by setting rows_per_chunk

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bug cuIO good first issue libcudf
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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 Oct 13, 2020
  • Java
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 Oct 11, 2020
  • Python

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 Nov 11, 2020
  • R

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