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Minor update on the key concept explanation (#28032)

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Amin Allahyar 2022-08-26 19:57:58 +02:00 • committed by GitHub
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doc/source/tune/key-concepts.rst
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@ -15,7 +15,7 @@ First, you define the hyperparameters you want to tune in a `search space` and p
that specifies the objective you want to tune.
Then you select a `search algorithm` to effectively optimize your parameters and optionally use a
`scheduler` to stop searches early and speed up your experiments.
Together with other configuration, your `trainable`, algorithm, and scheduler are passed into ``Tuner``,
Together with other configuration, your `trainable`, search algorithm, and scheduler are passed into ``Tuner``,
which runs your experiments and creates `trials`.
These trials can then be used in `analyses` to inspect your experiment results.
The following figure shows an overview of these components, which we cover in detail in the next sections.