Hyperparameters optimization packages for ML application in Julia

Hi all,

I am currently working with Flux.jl package for deep learning model implementation. I was wondering if some of you have had experience with some hyperparameters optimization packages (e.g. using hyperbands optimization algorithm) that can be nicely coupled with Flux.jl.

Thanks for sharing your experiences.

Simon.

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An implementation of hyperband is provided in https://github.com/baggepinnen/Hyperopt.jl#hyperband

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Another option: https://github.com/DrChainsaw/NaiveGAflux.jl

I guess it is has some half accidental similarity to hyperband in the sense that it tries to focus training efforts on promising candidates.

If one does not believe in parameter reuse it should be possible to build hyperband on it, e.g. by using elite selection of half the population size until there is only one candidate.

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