MLJ.jl

A Julia machine learning framework (by alan-turing-institute)

MLJ.jl Alternatives

Similar projects and alternatives to MLJ.jl

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better MLJ.jl alternative or higher similarity.

MLJ.jl reviews and mentions

Posts with mentions or reviews of MLJ.jl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-30.
  • What is the Julia equivalent of Scikit-Learn?
    3 projects | /r/Julia | 30 Dec 2022
    MLJ.jl is a good Julia ML framework. There's also a Scikitlearn.jl but its more of a wrapper around the sklearn I believe
  • My experience working as a technical writer for MLJ
    1 project | /r/Julia | 23 Nov 2022
    MLJ is a machine learning framework for Julia, which you can kind of infer from the article but it's not super obvious IMO.
  • [N] New BetaML v0.8: model definition, hyperparameters tuning and fitting in 2 lines
    2 projects | /r/MachineLearning | 2 Oct 2022
    The Beta Machine Learning Toolkit is a package including many algorithms and utilities to implement machine learning workflows in Julia, with a detailed tutorial on its usage from Python or R (no wrapper packages are needed) and an extensive interface to MLJ.
  • Python vs Julia
    3 projects | /r/Julia | 3 Aug 2021
    You should definitely go with Julia. It has steeper learning curve than python, but it is way more powerful. As for the ecosystem, you shouldn't worry about that much: DataFrames.jl and friends is way better than pandas, MLJ.jl (https://github.com/alan-turing-institute/MLJ.jl) and FastAI.jl(https://github.com/FluxML/FastAI.jl) are great frameworks for regular ML and deepnet. And if at any point you get a feeling that you need some python library, you can always plug it in with PyCall.jl(https://github.com/JuliaPy/PyCall.jl).
  • sklearn equivalent for Julia?
    3 projects | /r/Julia | 14 Apr 2021
    Imho, Julia is more diverse in the sense that there is not a single popular ML library. Maybe the Julian equivalent for scikit-learn is MLJ.jl. There is also ScikitLearn.jl, which defines the usual interface of scikit-learn models, and specific algorithms then implement this interface.
  • Swift for TensorFlow Shuts Down
    13 projects | news.ycombinator.com | 12 Feb 2021
    Then you haven't looked at Julia's ecosystem.

    It may not be quite as mature, but it's getting there quickly.

    It's also far more interoperable because of Julia's multiple dispatch and abstract types.

    For example, the https://github.com/alan-turing-institute/MLJ.jl ML framework (sklearn on steroids), works with any table object that implements the Tables.jl interface out of the box, not just with dataframes.

    That's just one example.

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    www.influxdata.com | 25 Apr 2024
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