Really looking forward to testing this out. Fortunately, I have a project ready to go for it...
One of the projects we released recently: Keras Tuner. A dedicated framework for hyperparameter tuning for Keras models https://keras-team.github.io/keras-tuner/
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I can't wait to use this. A hyperparameter tuning tool for Keras is something I am dreaming about for months now! My GridSearch on shell days are over finally!
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Nice work. It's amazing really that a framework for hyperparameter tuning has taken this long to come to the fore, it's just so obvious. Same applies for handling missing training data - err... hello!
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Do you prefer using the Learning Rate Scheduler Callback or the hp.Choice(“learning_rate”, values=[...]) in the optimizer?
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