Showing 32 open source projects for "machine learning projects"

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  • 1
    DiffEqOperators.jl

    DiffEqOperators.jl

    Linear operators for discretizations of differential equations

    DiffEqOperators.jl is a package for finite difference discretization of partial differential equations. It allows building lazy operators for high order non-uniform finite differences in an arbitrary number of dimensions, including vector calculus operators. For the operators, both centered and upwind operators are provided, for domains of any dimension, arbitrarily spaced grids, and for any order of accuracy. The cases of 1, 2, and 3 dimensions with an evenly spaced grid are optimized with...
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  • 2
    Augmentor.jl

    Augmentor.jl

    A fast image augmentation library in Julia for machine learning

    A fast library for increasing the number of training images by applying various transformations. Augmentor is a real-time image augmentation library designed to render the process of artificial dataset enlargement more convenient, less error prone, and easier to reproduce. It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. In other words, an augmentation pipeline is little more but a...
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  • 3
    SciMLTutorials.jl

    SciMLTutorials.jl

    Tutorials for doing scientific machine learning (SciML)

    SciMLTutorials.jl holds PDFs, webpages, and interactive Jupyter notebooks showing how to utilize the software in the SciML Scientific Machine Learning ecosystem. This set of tutorials was made to complement the documentation and the devdocs by providing practical examples of the concepts. For more details, please consult the docs. To view the SciML Tutorials, go to tutorials.sciml.ai. By default, this will lead to the latest tagged version of the tutorials
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  • 4
    Chess.jl

    Chess.jl

    Julia chess programming library

    ...There are functions for creating and manipulating chess games, chess positions and sets of squares on the board, for reading and writing chess games in the popular PGN format (including support for comments and variations), for creating opening trees, and for interacting with UCI chess engines. The library was designed for the purpose of doing machine learning experiments in computer chess, but it should also be suitable for most other types of chess software.
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  • 5
    MLDataUtils.jl

    MLDataUtils.jl

    Utility package for generating, loading, and processing ML datasets

    This package is designed to be the end-user facing front-end to all the data related functionality that is spread out across the JuliaML ecosystem. Most of the following sub-categories are covered by a single back-end package that is specialized on that specific problem. Consequently, if one of the following topics is of special interest to you, make sure to check out the corresponding documentation of that package.
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  • 6
    TensorFlow.jl

    TensorFlow.jl

    A Julia wrapper for TensorFlow

    A wrapper around TensorFlow, a popular open-source machine learning framework from Google.
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  • 7
    Merlin.jl

    Merlin.jl

    Deep Learning for Julia

    Merlin is a deep learning framework written in Julia. It aims to provide a fast, flexible and compact deep learning library for machine learning. Merlin is tested against Julia 1.0 on Linux, OS X, and Windows (x64).
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