# \[ANN\] LearnAPI.jl - Proposal for a basement-level machine learning API

**URL:** <https://discourse.julialang.org/t/ann-learnapi-jl-proposal-for-a-basement-level-machine-learning-api/93048>\
**Category:** Package Announcements\
**Created:** [January 16, 2023, 8:42pm UTC](https://discourse.julialang.org/t/ann-learnapi-jl-proposal-for-a-basement-level-machine-learning-api/93048 "2023-01-16T20:42:55Z")\
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**Author:** ![ablaom](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ablaom/32/4889_2.png) [@ablaom](https://discourse.julialang.org/u/ablaom)\
**Post date:** [January 16, 2023, 8:42pm UTC](https://discourse.julialang.org/t/ann-learnapi-jl-proposal-for-a-basement-level-machine-learning-api/93048/1 "2023-01-16T20:42:56Z")

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Feedback is being sought on a new, detailed proposal, called [LearnAPI.jl](https://github.com/JuliaAI/LearnAPI.jl), for a general purpose **low-level** machine learning interface. The proposal is based on our three years’ experience developing and maintaining the machine learning toolbox [MLJ.jl](https://alan-turing-institute.github.io/MLJ.jl/dev/). Ultimately, it may replace the current foundation of the MLJ ecosystem, but:

1. Is less tied to specific requirements of MLJ

2. Is extensively and more clearly documented (with a User Guide also planned)

3. Is easier for existing model implementations to adopt (e.g., no abstract model types to subtype)

4. Is general enough to accommodate the large variety of machine models already integrated with MLJ and more

5. Is agnostic to the form of data consumed by models. Using an optional data interface, each model articulates how user-provided data is coerced to model-specific representations (if these are different) and how observations within the data can be accessed (to allow for external control in resampling, for example).

To be clear, this proposal concerns a low level API, not a full blown ML toolbox.

For details, visit the [docs](https://juliaai.github.io/LearnAPI.jl/dev/).

Feedback welcome here, on the #mlj Julia slack channel, or, to provide private feedback, direct message me on Julia slack. My handle is `@ablaom`.

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