Showing 4 open source projects for "c programming framework"

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  • 1
    .NET for Apache Spark

    .NET for Apache Spark

    A free, open-source, and cross-platform big data analytics framework

    .NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations.
    Downloads: 1 This Week
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  • 2

    X10

    Performance and Productivity at Scale

    X10 is a class-based, strongly-typed, garbage-collected, object-oriented language. To support concurrency and distribution, X10 uses the Asynchronous Partitioned Global Address Space programming model (APGAS). This model introduces two key concepts -- places and asynchronous tasks -- and a few mechanisms for coordination. With these, APGAS can express both regular and irregular parallelism, message-passing-style and active-message-style computations, fork-join and bulk-synchronous...
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    Downloads: 2 This Week
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  • 3
    Exl2Sql

    Exl2Sql

    Excel to SQL

    This tool will convert an Excel Spreadsheet (.xls and .xlsx files) into SQL INSERTs to one table. The first row of your excel sheet will be used as the column names so you cannot have any NULL values. Then the data underneath the column name is applied into that column with the generated insert statement. You can Save or Copy the data and then use Find and Replace if you need to tweak. Good for big data. Needed this for my work so created over the weekend, happy to share with the...
    Downloads: 0 This Week
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  • 4

    Random Bits Forest

    RBF: a Strong Classifier/Regressor for Big Data

    We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. In conclusion, RBF is a novel framework that performs strongly especially on data...
    Downloads: 0 This Week
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