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  • Gemini 3 and 200+ AI Models on One Platform Icon
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  • 1
    Vespa

    Vespa

    The open big data serving engine

    ...Vespa is a full-featured text search engine and supports both regular text search and fast approximate vector search (ANN). This makes it easy to create high-performing search applications at any scale, whether you want to use traditional techniques or a modern vector-based approach. You can even combine both approaches efficiently in the same query, something no other engine can do. Recommendation, personalization and targeting involves evaluating recommender models over content items to select the best ones. Vespa lets you build applications which does this online, typically combining fast vector search and filtering with evaluation of machine-learned models over the items. ...
    Downloads: 7 This Week
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  • 2
    Apache HBase

    Apache HBase

    Get random, realtime read/write access to your Big Data

    Use Apache HBase™ when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables, billions of rows X millions of columns, atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable. A Distributed Storage System for Structured Data by Chang et al.
    Downloads: 9 This Week
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  • 3
    apache spark data pipeline osDQ

    apache spark data pipeline osDQ

    osDQ dedicated to create apache spark based data pipeline using JSON

    ...\example\samplerun.json Mac UNIX java -cp ./lib/*:./osdq-spark-0.0.1.jar org.arrah.framework.spark.run.TransformRunner -c ./example/samplerun.json For those on windows, you need to have hadoop distribtion unzipped on local drive and HADOOP_HOME set. Also copy winutils.exe from here into HADOOP_HOME\bin
    Downloads: 1 This Week
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  • 4
    DSTK - DataScience ToolKit

    DSTK - DataScience ToolKit

    DSTK - DataScience ToolKit for All of Us

    ...Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify JASP for advanced data editing and RapidMiner for advanced prediction modeling. DSTK is written in C#, Java and Python to interface with R, NLTK, and Weka. It can be expanded with plugins using R Scripts. We have also created plugins for more statistical functions, and Big Data Analytics with Microsoft Azure HDInsights (Spark Server) with Livy. ...
    Downloads: 0 This Week
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