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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.).

zerocode-tdd is a community-developed, free, open-source, outcome-driven automated testing framework for Data Pipelines, ETL, REST API, Kafka(Data Streams), Databases and Load scenarios. all defined in simple JSON or YAML — with zero coding.

  • soap
  • assertions
  • java
  • api

Angora is a mutation-based fuzzer. The main goal of Angora is to increase branch coverage by solving path constraints without symbolic execution.

GenFu is a library you can use to generate realistic test data. It is composed of several property fillers that can populate commonly named properties through reflection using an internal database of values or randomly created data. You can override any of the fillers, give GenFu hints on how to fill them.

:heavy_check_mark: Mock data for your prototypes and demos. Remote deployments to Zeit now.

  • atmo
  • prototyping
  • mock-services
  • mock-server