MlJ.jl: A Julia Machine Learning Framework

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com
Julia Machine Learning Pipeline Mlj package-manager

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  • AutoMLPipeline.jl

    A package that makes it trivial to create and evaluate machine learning pipeline architectures.

  • Pkg.jl

    Pkg - Package manager for the Julia programming language

    • This is exacerbated by the fact that Julia's Pkg.jl does not yet support conditional/optional dependencies [0]. A lot of these meta packages tend to pull everything but the kitchen sink.

    [0]: https://github.com/JuliaLang/Pkg.jl/issues/1285

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • maptrace

    Produce watertight polygonal vector maps by tracing raster images

    • How far could you go with some automatic cleaning, something like `maptrace` [0] and some topology rules when you have your vector file to finish with some manual artistic polish? Because, i don't believe that you will achieve easily the "do-it-like-me" result expected from either GAN or VAE or autoencoders. In case of you want to look, the classic examples about style transfer (Photo to Van Gogh style, etc.) seems to be the way to go. Specific to Julia, you can look at Flux.jl or KNet.jl.

    [0] https://github.com/mzucker/maptrace

  • ScientificTypes.jl

    An API for dispatching on the "scientific" type of data instead of the machine type

    • Sorry, I don't have a good introduction to recommend, I just wanted to include a link if anyone is intrigued by "scientific types", which refers specifically to: https://github.com/alan-turing-institute/ScientificTypes.jl

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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