Showing 3 open source projects for "machine learning python"

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    The HaskellR project

    The HaskellR project

    The full power of R in Haskell

    ...HaskellR allows Haskell functions to seamlessly call R functions and vice versa. It provides the Haskell programmer with the full breadth of existing R libraries and extensions for numerical computation, statistical analysis and machine learning. Optionally, pass in the --nix flag to all commands if you have the Nix package manager installed. Nix can populate a local build environment including all necessary system dependencies without touching your global filesystem. Use it as a cross-platform alternative to Docker.
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  • 2
    TensorFlow Haskell

    TensorFlow Haskell

    Haskell bindings for TensorFlow

    The tensorflow-haskell package provides Haskell-language bindings for TensorFlow, giving Haskell developers the ability to build and run computation graphs, machine learning models, and leverage TensorFlow's ecosystem—though it is not an official Google release. As an expedient we use docker for building. Once you have docker working, the following commands will compile and run the tests. Run the install_macos_dependencies.sh script in the tools/ directory. The script installs dependencies via Homebrew and then downloads and installs the TensorFlow library on your machine under /usr/local. ...
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  • 3
    Functional-Programming

    Functional-Programming

    Functional Programming concepts, examples and patterns

    This repository is a tutorial collection showcasing functional programming concepts across multiple languages (Haskell, OCaml, Scala, Scheme, Clojure, Python). It provides reusable code snippets, examples, and case studies to illustrate FP ideas in a comparative manner. The purpose of this tutorial is to illustrate functional programming concepts in many languages by providing reusable and useful snippets of code, examples, case studies and applications. The project’s web site was updated...
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