Kubeflow pipelines quickstart notebooks added.

[ghost]

This change is 

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[k8s-ci-robot]

Hi @rostam-github. Thanks for your PR.

I'm waiting for a kubeflow member to verify that this patch is reasonable to test. If it is, they should reply with /ok-to-test on its own line. Until that is done, I will not automatically test new commits in this PR, but the usual testing commands by org members will still work. Regular contributors should join the org to skip this step.

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[k8s-ci-robot]

Hi @rostam-github. Thanks for your PR.

I'm waiting for a kubeflow member to verify that this patch is reasonable to test. If it is, they should reply with /ok-to-test on its own line. Until that is done, I will not automatically test new commits in this PR, but the usual testing commands by org members will still work. Regular contributors should join the org to skip this step.

Once the patch is verified, the new status will be reflected by the ok-to-test label.

I understand the commands that are listed here.

Instructions for interacting with me using PR comments are available here. If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository.

[vicaire]

Hi @rostam-github,

Could you please follow the instruction to pass the CLA test?

[googlebot]

CLAs look good, thanks!

[neuromage]

/ok-to-test

[vicaire]

Hi @rostam-github,

Could you please provide some info about how this quickstart notebook is different from the ones we already provide?

We don't have e2e tests for notebooks yet so we are a little reticent to accept new samples except if they illustrate a particularly interesting case, or something that's missing from our existing notebooks.

[ghost]

Hi @vicaire ,
It is a stand alone notebook tutorial, that is, you can run the entire process of creating a Kubeflow pipeline from start to end all in the same notebook. I created it for me because it was helpful to see the entire process in one place rather than jumping from page to page in the current tutorials for different snippets. I shared it with a customer and they had great feedback too. In google3 we don't write tests for Colab notebooks.

[vicaire]

Thanks you.

Could you please compare to the existing notebook samples (I am not sure whether you are aware of them)?

https://github.com/kubeflow/pipelines/tree/master/samples/notebooks

Does it illustrate additional concepts? Would it make sense to merge this notebook with existing ones? Or does it introduces enough new concepts (without duplication)?

[ghost]

Thanks Pascal. Those two code samples don't have any info about how to build your image and put it Container Registry (which is probably more confusing for data scientists, because they are usually very comfortable with Python). There are some duplicates, for example, the first notebook contains a sample for lightweight implementation as one of the ways to create a component, but then it explains the other method in the same place. There are duplications between all of them. Can we do a quick hangout and quickly discuss this?

[neuromage]

Rostam, I can review this PR and coordinate with you. Would you like to schedule a quick hangout as suggested? I am free this afternoon, or we can aim to discuss on Tuesday as well.

High-level comments:

• Let's move this into /samples/notebooks/
• It looks like quickstart1 is about component authoring and what one can do in a component, while the second is about how to stitch them into a pipeline. Is this correct? If so, maybe we can update the names of the files and headers to indicate that.
• Would you be up to adding more text/description on the steps? Currently, it's mostly sample code, while for a notebook, having more in-depth explanation of what's going could be useful as well.

Also, many thanks for taking the time to submit the PR!

[ghost]

Hi Ajay,
Thank you for your great comments! I incorporate them. Please review.
Best,
Rostam

[neuromage]

Thanks for the PR, and apologies for the delayed review. Overall looks good. Thanks!

[ghost]

Thank you for reviewing. I incorporated the comments. Please review.

[vicaire]

@neuromage, @gaoning777, do you have further comments? Can we approve?

[gaoning777]

\lgtm

[gaoning777]

Add an issue to add the sample test: #1224

[gaoning777]

Thanks @rostam-github for your contribution and sorry that this PR merging took so long.

/approve

[k8s-ci-robot]

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: gaoning777

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[k8s-ci-robot]

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: gaoning777

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• samples/OWNERS [gaoning777]

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[ghost]

Thank you for review and great comments!

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