Showing 4 open source projects for "java machine learning library"

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    The Julia Programming Language

    The Julia Programming Language

    High-level, high-performance dynamic language for technical computing

    Julia is a fast, open source high-performance dynamic language for technical computing. It can be used for data visualization and plotting, deep learning, machine learning, scientific computing, parallel computing and so much more. Having a high level syntax, Julia is easy to use for programmers of every level and background. Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose computing. ...
    Downloads: 9 This Week
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  • 2
    Lux

    Lux

    The Lux Programming Language

    Lux is a new programming language in the making. It's meant to be a functional, statically-typed Lisp that will run on several platforms, such as the Java Virtual Machine and JavaScript, Python, Lua, or Ruby interpreters. Lux is in the beta stage. The JVM compiler is pretty stable and the standard library has grown to a respectable size. Also, new experimental support for JavaScript, Python, Lua, and Ruby has been added. Read carefully before using this project, as the license disallows commercial use, and has other conditions which may be undesirable for some. ...
    Downloads: 1 This Week
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  • 3

    Seed7

    Interpreter and compiler for the Seed7 programming language.

    Interpreter, compiler, libraries, documentation and examples for the Seed7 programming language. Seed7 is a general purpose programming language. It is a higher level language compared to Ada, C/C++ and Java. In Seed7 new statements and operators can be declared easily. Functions with type results and type parameters are more elegant than a template or generics concept. Object orientation is used where it brings advantages and not in places where other solutions are more obvious. Seed7...
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    Downloads: 38 This Week
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  • 4
    Edward

    Edward

    A probabilistic programming language in TensorFlow

    ...Edward fuses three fields, Bayesian statistics and machine learning, deep learning, and probabilistic programming. Edward is built on TensorFlow. It enables features such as computational graphs, distributed training, CPU/GPU integration, automatic differentiation, and visualization with TensorBoard. Expectation-Maximization, pseudo-marginal and ABC methods, and message passing algorithms.
    Downloads: 2 This Week
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