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Fixes #1316 (#1620)
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* Show which version of Kubeflow works for each sample project (#1316)

This commit will fetch the commit history from sample project to
determine when was the last time that the project received an
Updated.

* Fixed typo

This PR accidentally changed "repo" to "Rep". I've fixed that, and at the same time decided to use the full term instead of the original abbreviation.

* Removed misplaced line of text

This PR mistakenly copy-pasted a line of text from the financial time series sample into the issue summarization sample. I've removed the line.

Co-authored-by: Sarah Maddox <[email protected]>
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hefedev and sarahmaddox authored Feb 10, 2020
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93 changes: 50 additions & 43 deletions content/docs/examples/kubeflow-samples.md
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Expand Up @@ -4,50 +4,57 @@ description = "Examples that demonstrate machine learning with Kubeflow"
weight = 10
+++

{{% blocks/content-item %}}
This section introduces the examples in the
[kubeflow/examples](https://github.com/kubeflow/examples) repo.
{{% /blocks/content-item %}}

{{% blocks/content-item title="Semantic code search"
url="https://github.com/kubeflow/examples/tree/master/code_search" %}}
Use a Sequence to Sequence natural language processing model to perform a semantic code search. This tutorial runs in a Jupyter notebook and uses Google Cloud Platform (GCP).
{{% /blocks/content-item %}}

{{% blocks/content-item title="Financial time series"
url="https://github.com/kubeflow/examples/tree/master/financial_time_series" %}}
Train and serve a model for financial time series analysis using TensorFlow
on GCP.
{{% /blocks/content-item %}}


{{% blocks/content-item title="GitHub issue summarization"
url="https://github.com/kubeflow/examples/tree/master/github_issue_summarization" %}}
Infer summaries of GitHub issues from the descriptions, using a Sequence to
Sequence natural language processing model. You can run the tutorial in a
Jupyter notebook or using TFJob. You use Seldon Core to serve the model.
{{% /blocks/content-item %}}

{{% blocks/content-item title="MNIST image classification"
url="https://github.com/kubeflow/examples/tree/master/mnist" %}}
Train and serve an image classification model using the MNIST dataset. You can
choose to train the model locally, using GCP, or using Amazon S3. Serve the
model using TensorFlow.
{{% /blocks/content-item %}}

{{% blocks/content-item title="Object detection - cats and dogs"
url="https://github.com/kubeflow/examples/tree/master/object_detection" %}}
Train a distributed model for recognizing breeds of cats and
dogs with the TensorFlow Object Detection API. Serve the model using TensorFlow.
{{% /blocks/content-item %}}

{{% blocks/content-item title="PyTorch MNIST"
url="https://github.com/kubeflow/examples/tree/master/pytorch_mnist" %}}
This section introduces the examples in the [Kubeflows/examples](https://github.com/kubeflow/example) repository.

{{% blocks/sample-section title="Financial time series"
kfctl="v0.7"
url="https://github.com/kubeflow/examples/tree/master/financial_time_series"
api="https://api.github.com/repos/kubeflow/examples/commits?path=financial_time_series&sha=master" %}}
Train and serve a model for financial time series analysis using TensorFlow on GCP.
{{% /blocks/sample-section %}}

{{% blocks/sample-section title="GitHub issue summarization"
kfctl="v0.3.0-rc.3"
url="https://github.com/kubeflow/examples/tree/master/github_issue_summarization"
api="https://api.github.com/repos/kubeflow/examples/commits?path=github_issue_summarization&sha=master" %}}
Infer summaries of GitHub issues from the descriptions, using a Sequence to Sequence natural language processing model.
You can run the tutorial in a Jupyter notebook or using TFJob. You use Seldon Core to serve the model.
{{% /blocks/sample-section %}}

{{% blocks/sample-section title="MNIST image classification"
kfctl=""
url="https://github.com/kubeflow/examples/tree/master/mnist"
api="https://api.github.com/repos/kubeflow/examples/commits?path=mnist&sha=master" %}}
Train and serve an image classification model using the MNIST dataset.
You can choose to train the model locally, using GCP, or using Amazon S3. Serve the model using TensorFlow.
{{% /blocks/sample-section %}}

{{% blocks/sample-section title="Object detection - cats and dogs"
kfctl=""
url="https://github.com/kubeflow/examples/tree/master/object_detection"
api="https://api.github.com/repos/kubeflow/examples/commits?path=object_detection&sha=master" %}}
Train a distributed model for recognizing breeds of cats and dogs with the TensorFlow Object Detection API. Serve the model using TensorFlow.
{{% /blocks/sample-section %}}

{{% blocks/sample-section title="PyTorch MNIST"
kfctl=""
url="https://github.com/kubeflow/examples/tree/master/pytorch_mnist"
api="https://api.github.com/repos/kubeflow/examples/commits?path=pytorch_mnist&sha=master" %}}
Train a distributed PyTorch model on GCP and serve the model with Seldon Core.
{{% /blocks/content-item %}}
{{% /blocks/sample-section %}}

{{% blocks/content-item title="Ames housing value prediction"
url="https://github.com/kubeflow/examples/tree/master/xgboost_ames_housing" %}}
{{% blocks/sample-section title="Ames housing value prediction"
kfctl=""
url="https://github.com/kubeflow/examples/tree/master/xgboost_ames_housing"
api="https://api.github.com/repos/kubeflow/examples/commits?path=xgboost_ames_housing&sha=master" %}}
Train an XGBoost model using the Kaggle Ames Housing Prices prediction on GCP.
Use Seldon Core to serve the model locally, or GCP to serve it in the cloud.
{{% /blocks/content-item %}}
{{% /blocks/sample-section %}}

{{% blocks/sample-section title="Semantic code search"
kfctl="0.3"
url="https://github.com/kubeflow/examples/tree/master/code_search"
api="https://api.github.com/repos/kubeflow/examples/commits?path=code_search&sha=master" %}}
Use a Sequence to Sequence natural language processing model to perform a semantic code search.
This tutorial runs in a Jupyter notebook and uses Google Cloud Platform (GCP).
{{% /blocks/sample-section %}}
10 changes: 10 additions & 0 deletions layouts/shortcodes/blocks/sample-section.html
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{{ $api := .Get "api" }}
{{ $last_updated := "" }}
{{ $version := .Get "kfctl" }}
<div class="col-lg-12 mb-5 mb-lg-0 ">
{{ with .Get "title" }}<h4 class="h3 mt-3">{{ . }}</h4>{{ end }}
{{ with getJSON $api }} {{ $last_updated = (index (index (index (index . 0) "commit") "committer") "date") | dateFormat "2006/01/02" }}
<p class="text-muted">{{ "Last update " }} {{ $last_updated }} {{ with $version }}{{ "Kubeflow " }}{{ . }}{{ end }}</p>{{ end }}
<p class="mb-0">{{ .Inner }}</p>
{{ with .Get "url" }}<p><a href="{{ . }}">{{ "Go to sample" }}</a></p>{{ end }}
</div>

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