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@Juta Juta commented Feb 23, 2023

Restructure ML overview website page and add explanation about model validation


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Juta commented Feb 23, 2023

@damccorm Hi Danny, I made an additional edit to update the overview page of ML and to include model validation. Please have a look

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## Model validation

Model validation allows you to benchmark your model’s performance against an unseen dataset. You can extract chosen metrics, create visualizations, log metadata, and compare the performance of different models with the end goal of validating whether your model is ready to deploy. Beam provides support for running model evaluation on a TensorFlow model directly inside your pipeline.
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Suggested change
Model validation allows you to benchmark your model’s performance against an unseen dataset. You can extract chosen metrics, create visualizations, log metadata, and compare the performance of different models with the end goal of validating whether your model is ready to deploy. Beam provides support for running model evaluation on a TensorFlow model directly inside your pipeline.
Model validation allows you to benchmark your model’s performance against a previously unseen dataset. You can extract chosen metrics, create visualizations, log metadata, and compare the performance of different models with the end goal of validating whether your model is ready to deploy. Beam provides support for running model evaluation on a TensorFlow model directly inside your pipeline.

Small wording nit

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Thanks, this LGTM other than the 2 small comments

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Juta commented Feb 24, 2023

Thanks @damccorm. I made the requested changes

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retest this please

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(comment is for bot)

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Run RAT PreCommit

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Thanks!

@damccorm damccorm merged commit bddfd86 into apache:master Feb 24, 2023
ruslan-ikhsan pushed a commit to akvelon/beam that referenced this pull request Mar 10, 2023
* restructure ml overview website page

* small edits ML website
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