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Oryx download for Windows

Free download Oryx Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named Oryx whose latest release can be downloaded as Oryx2.8.0.zip. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named Oryx with OnWorks for free.

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- 6. Download the application and install it.

- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

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Oryx


DESCRIPTION

Oryx 2 is a realization of the lambda architecture built on Apache Spark and Apache Kafka, but with specialization for real-time large-scale machine learning. It is a framework for building applications but also includes packaged, end-to-end applications for collaborative filtering, classification, regression and clustering. The application is written in Java, using Apache Spark, Hadoop, Tomcat, Kafka, Zookeeper and more. Configuration uses a single Typesafe Config config file, wherein applications configure an entire deployment of the system. This includes implementations of key interface classes which implement the batch, speed, and serving logic. Applications package and deploy their implementations with each instance of the layer binaries. Each of these is a runnable Java .jar which starts all necessary services.



Features

  • Generic lambda architecture tier, providing batch/speed/serving layers, which is not specific to machine learning
  • Specialization on top providing ML abstractions for hyperparameter selection, etc.
  • End-to-end implementation of the same standard ML algorithms as an application (ALS, random decision forests, k-means) on top
  • The data transport mechanism is an Apache Kafka topic
  • The speed layer is implemented as a Spark Streaming process
  • The batch layer is implemented as a Spark Streaming process on a Hadoop cluster


Programming Language

Java


Categories

Machine Learning

This is an application that can also be fetched from https://sourceforge.net/projects/oryx.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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