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The V Machine Learning Roadmap and Ecosystem #12535

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ulises-jeremias opened this issue Nov 21, 2021 · 3 comments
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The V Machine Learning Roadmap and Ecosystem #12535

ulises-jeremias opened this issue Nov 21, 2021 · 3 comments
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@ulises-jeremias
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ulises-jeremias commented Nov 21, 2021

This issue defines a first iteration of the Machine Learning Roadmap. All the specific tasks will be linked to each corresponding repository and also contained on the ML Project here.

We can think a ML Ecosystem as a composition of five different categories: Array Protocols, Foundation, Technique Specific, Domain-Specific and Application Specific.

Array Protocols

For this category we seek to have an alternative implementation to arrays in V. In V it is not possible to create a structure that uses the same operators as an array, so it is not possible to implement a structure that has the same protocol as an array.

However, we started working on VTL, a library similar to numpy, arraymance, among others that offers a Ndarray (in this case called Tensor).

Foundation

On this category I identify two aspects: Algorithms and Plotting tools.
On this area we did a cool progress and we already have some libraries for this:

  • V Scientific Library, VSL., is a library with a great variety of different modules. Although most modules offer pure-V definitions, VSL also provides modules that wrap known C libraries among other backends that allow high performance computing as an alternative.
  • vsl.plot is the plot submodule of VSL that follows the structure of
    Plotly's graph_objects to plot data. Will provide more backends in the future and also a pure V implementation at some point.

Thirdparty

Technique Specific

  • vsl.ml has Kmeans, LinearRegression, KNN, Params Regression, NLP, and a Data wrapper with an observer pattern.
  • . . .

Thirdparty

  • hamnn is a machine learning library for classification using a nearest neighbor algorithm based on Hamming distances.
  • vervet is a Dataframe manipulation tool written in V

Domain Specific

TODO

Application Specific

TODO

@ulises-jeremias ulises-jeremias created this issue from a note in Machine Learning Roadmap (To do) Nov 21, 2021
@ulises-jeremias ulises-jeremias moved this from To do to Done in Machine Learning Roadmap Nov 21, 2021
@ulises-jeremias ulises-jeremias self-assigned this Nov 21, 2021
@ulises-jeremias ulises-jeremias moved this from Done to In progress in Machine Learning Roadmap Nov 21, 2021
@danieldaeschle
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A keras/tf implementation would also be nice!

@ulises-jeremias
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@danieldaeschle sure! an initial iteration of that will be covered when https://github.com/vlang/vtl/tree/main/nn gets released! it is still WIP

@ArtemkaKun
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@ulises-jeremias Hi, maybe we should close/update/move this issue?

@vlang vlang locked and limited conversation to collaborators Sep 17, 2023
@ArtemkaKun ArtemkaKun converted this issue into discussion #19371 Sep 17, 2023

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