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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.).

This repository is designed to create an enterprise Blazor Server application that follows the principles of Clean Architecture and implements Blazor Clean Architecture best practices for scalability, maintainability, and testability.

  • clean-architecture
  • best-practices
  • blazor-boilerplate
  • blazor-server-template

:lipstick: Durable and asynchronous data imports for consuming data at scale and publishing testable SDKs.

  • porter
  • data-import
  • framework
  • data-transformation

One database for user-user (follows), user-item (likes), and item-item (related items) interactions — precomputed at write time, served as simple lookups

The Coherence Go Client allows native Go applications to act as cache clients to a Coherence cluster using gRPC for the network transport.

  • coherence
  • coherence-ce
  • golang
  • grpc

Vertx-effect brings functional effects to the Vert.x ecosystem and is inspired by Erlang’s actor model. Its manifesto emphasizes principles such as maximizing the use of verticles for scalability, maintaining single responsibility for each verticle, and prioritizing simplicity to enhance reliability and ease debugging.

  • functional-programming
  • java
  • json-values
  • persistent-data-structure