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.).
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Base classes to use when writing tests with Spark
PySpark test helper methods with beautiful error messages
Benchmarks for Low Latency (Streaming) solutions including Apache Storm, Apache Spark, Apache Flink, ...
- benchmarks
- low-latency
- streaming
Apache Spark testing helpers (dependency free & works with Scalatest, uTest, and MUnit)