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A repository to host extended examples and tutorials
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Sanyam Kapoor c1b2802313 Add new TF-Serving component with sample task (#152) 
* Add new TF-Serving component with sample task

* Unify nmslib and t2t packages, need to be cohesive

* [WIP] update references to the package

* Replace old T2T problem

* Add representative code for encoding/decoding from tf serving service

* Add rest API port to TF serving (replaces custom http proxy)

* Fix linting

* Add NMSLib creator and server components

* Add docs to CLI module
 		2018-06-28 20:37:21 -07:00
agents Restore runnability of example; vendor agnostic storage (#72) 2018-04-06 21:37:08 -07:00
code_search Add new TF-Serving component with sample task (#152) 2018-06-28 20:37:21 -07:00
github_issue_summarization Add component parameters (#155) 2018-06-28 13:52:21 -07:00
mnist Fixed distributed training for LINEAR model (#130) 2018-06-13 11:57:28 -07:00
test/workflows Fix failing test due to https://github.com/kubeflow/testing/pull/111 (#95) 2018-04-24 12:11:00 -07:00
.gitignore Make it easier to demo serving and run in Katacoda (#107) 2018-04-28 08:11:18 -07:00
.pylintrc Add namespace to ksonnet apply command (#57) 2018-04-02 09:41:02 -07:00
CONTRIBUTING.md Tune application-focused description (#124) 2018-06-06 19:56:24 -07:00
LICENSE Initial commit 2018-02-01 13:13:10 -08:00
OWNERS Add cwbeitel reviewer & texasmichelle approver (#64) 2018-03-29 15:21:03 -07:00
README.md Proposed repo strategy (#117) 2018-06-05 09:57:57 -07:00
prow_config.yaml Skeleton testing framework (#18) 2018-03-01 21:30:50 -08:00

README.md

kubeflow-examples

A repository to share extended Kubeflow examples and tutorials to demonstrate machine learning concepts, data science workflows, and Kubeflow deployments. They illustrate the happy path, acting as a starting point for new users and a reference guide for experienced users.

This repository is home to three types of examples:

  1. End-to-end
  2. Component-focused
  3. Application-specific

End-to-end

GitHub issue summarization

Author: Hamel Husain

This example covers the following concepts:

  1. Natural Language Processing (NLP) with Keras and Tensorflow
  2. Connecting to Jupyterhub
  3. Shared persistent storage
  4. Training a Tensorflow model
  5. CPU
  6. GPU
  7. Serving with Seldon Core
  8. Flask front-end

MNIST

Author: Elson Rodriguez

This example covers the following concepts:

  1. Image recognition of handwritten digits
  2. S3 storage
  3. Training automation with Argo
  4. Monitoring with Argo UI and Tensorboard
  5. Serving with Tensorflow

Component-focused

Application-specific

Third-party hosted

Source Example Description

Get Involved

In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation.

The Kubeflow community is guided by our Code of Conduct, which we encourage everybody to read before participating.