Showing 4 open source projects for "squid-graph"

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    Apache Spark

    Apache Spark

    A unified analytics engine for large-scale data processing

    Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing.
    Downloads: 1 This Week
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    sbt

    sbt

    sbt, the interactive build tool

    ...One of the examples of a Scala-specific feature is the ability to cross-build your project against multiple Scala versions. build.sbt is a Scala-based DSL to express parallel processing task graph. Typos in build.sbt will be caught as a compilation error. With Zinc incremental compiler and file watch (~), edit-compile-test loop is fast and incremental. Adding support for new tasks and platforms (like Scala.js) is as easy as writing build.sbt. Join 100+ community-maintained plugins to share and reuse sbt tasks. Continuous compilation and testing with triggered execution. ...
    Downloads: 1 This Week
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  • 3
    node2vec

    node2vec

    Learn continuous vector embeddings for nodes in a graph using biased R

    ...It allows researchers and practitioners to apply node2vec to various graph datasets and evaluate embedding quality on downstream tasks. By bridging ideas from graph theory and word embedding models, this project demonstrates how graph-based machine learning can be made efficient and flexible.
    Downloads: 0 This Week
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  • 4
    Asteroid

    Asteroid

    A CBLS Engine in SCALA, NOW part of OscaR

    Asteroid has been merged with Scampi, to give rise to OScar. Follow us on https://bitbucket.org/oscarlib/oscar/wiki/Home Asteroid offers a powerful framework for developing constraint-based local search solution to combinatorial problems. This technique provides good scalability to real-world problems. It includes a library of standard constraints and invariants to declaratively define the problem you want to solve, and it also provides powerful search mechanisms.
    Downloads: 0 This Week
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