New version: MLJTuning v0.8.6

[JuliaRegistrator]

• Registering package: MLJTuning
• Repository: https://github.com/JuliaAI/MLJTuning.jl
• Created by: @ablaom
• Version: v0.8.6
• Commit: 1af0202b7fc256e03c15a9604696e6092a0b141e
• Reviewed by: @ablaom
• Reference: Issue for triggering new releases JuliaAI/MLJTuning.jl#59 (comment)
• Description: Hyperparameter optimization algorithms for use in the MLJ machine learning framework
• Release notes:

- (**new feature**) Add `logger` option to `TunedModel` wrapper, for logging internal model evaluations to an ML tracking platform,  such as MLflow via [MLJFlow.jl](https://github.com/JuliaAI/MLJFlow.jl). Default should be `nothing` for no logging (#193). The logger must support asynchronous messaging if `TunedModel(model, ...)` is specified with the option `acceleration=CPUThreads()` or `CPUProcesses()`. Currently, `CPU1()` (the default) is supported by MLJFlow.jl's loggers, while ansynchronous support is a work in progress; see https://github.com/JuliaAI/MLJFlow.jl/pull/41 #193.

[github-actions]

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