Showing 481 open source projects for "java software .jar"

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  • 1

    AntiPython-AI-Compiler-Colab

    Google Colab GPU access in your favorite programming language

    AntiPython Colab is a source to source compiler that let's you build AI in Java, Rust, JavaScript, Flutter, C#, Go, Ocaml(and etc...) utilizing free Google Colab GPUs! It's blazingly fast and very robust as it uses websockets and the Treesitter C library under the hood.
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  • 2
    eagle-i
    eagle-i is an ontology-driven, RDF-based distributed platform for creating, storing and searching semantically rich data. eagle-i is built around semantic web technologies and adheres to linked open data principles.
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  • 3
    Music agent is a software agent designed to help people discover new creative commons licensed music according to their personal taste.
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  • 4

    Solve Logic Word Puzzles with CLP

    Constraint Logic can solve word logic puzzles.

    Learn basic constraint logic programming by solving logic word puzzles. Go to http://eclipse.dougedmunds.com . This tutorial will show you how to solve easy 1 star to hard 5 star puzzles, using the eCLiPSe-CLP language (available at http://eclipseclp.org/). Don't confuse this programming language (a prolog language) with the IDE for Java.
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  • 5

    automated-linguistic-analysis

    Automated Linguistic Analysis, with both monolith and cluster versions

    Sample application showcasing usage of technologies such as: * OSGi R7 Promises for asynchronous generation of transcriptions and linguistic analyses * OSGi R7 Push Stream and JAX RS Server Sent Events for push notifications of processing status * Apache Camel 2.23.1 and RabbitMQ 3.7 for asynchronous communication between services * JPA 2.1 and Hibernate 5.2.12, along with OSGi R7 JPA and Transaction Control services, for persistence layer * OSGi R7 HTTP and JAX RS Whiteboard for...
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  • 6

    Supertagger

    Software for assigning supertags.

    Supertagging is a process of statistical lexical disambiguation, preprocessing step to parsing, which assigns LTAG tree categories to the lexical items present in the input sentence. Thus, if the input sentence is in the form of a dependency tree, the task of the supertagger is to assign the most probable TAG family to each node and edge in the dependency tree.
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