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Signed-off-by: Gong Sophia <sophia.gong@intel.com>
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Machine Learning
================
[![](https://images.microbadger.com/badges/image/clearlinux/machine-learning-ui.svg)](http://microbadger.com/images/clearlinux/machine-learning-ui "Get your own image badge on microbadger.com")
[![](https://images.microbadger.com/badges/version/clearlinux/machine-learning-ui.svg)](http://microbadger.com/images/clearlinux/machine-learning-ui "Get your own version badge on microbadger.com")
# Clear Linux* OS `machine-learning-ui` container image
This provides a machine learning environment with the `machine-learning-web-ui`,
bundle from [Clearlinux](https://clearlinux.org/documentation/bundles_overview.html)
<!-- Required -->
## What is this image?
Build
-----
```
docker build -t clearlinux/machine-learning-ui .
```
`clearlinux/machine-learning-ui` is a Docker image with `machine-learning-ui` running on top of the
[official clearlinux base image](https://hub.docker.com/_/clearlinux).
Or just pull it from Dockerhub
------------------------------
```
docker pull clearlinux/machine-learning-ui
```
<!-- application introduction -->
> Machine Learning UI provides the machine learning framework with Jupiter notebook with the
> benefits of Clear Linux OS.
Run the machine-learning-ui Container
----------------------------------
```
docker run -p 8888:8888 -it clearlinux/machine-learning-ui
```
For other Clear Linux* OS
based container images, see: https://hub.docker.com/u/clearlinux
Environment Variables
---------------------
none
## Why use a clearlinux based image?
Extra Build ARGs
----------------
- ``swupd_args`` Specifies [SWUPD](https://github.com/clearlinux/swupd-client/blob/master/docs/swupd.1.rst#options) flags
<!-- CL introduction -->
> [Clear Linux* OS](https://clearlinux.org/) is an open source, rolling release
> Linux distribution optimized for performance and security, from the Cloud to
> the Edge, designed for customization, and manageability.
Default build args in Docker are on: https://docs.docker.com/engine/reference/builder/#arg
Clear Linux* OS based container images use:
* Optimized libraries that are compiled with latest compiler versions and
flags.
* Software packages that follow upstream source closely and update frequently.
* An aggressive security model and best practices for CVE patching.
* A multi-staged build approach to keep a reduced container image size.
* The same container syntax as the official images to make getting started
easy.
To learn more about Clear Linux* OS, visit: https://clearlinux.org.
<!-- Required -->
## Deployment:
### Deploy with Docker
The easiest way to get started with this image is by simply pulling it from
Docker Hub.
1. Pull the image from Docker Hub:
```
docker pull clearlinux/machine-learning-ui
```
2. Start a container using the examples below:
```
docker run -p 8888:8888 -it clearlinux/machine-learning-ui
```
<!-- Optional -->
### Deploy with Kubernetes
This image can also be deployed on a Kubernetes cluster, such as
[minikube](https://kubernetes.io/docs/setup/learning-environment/minikube/).The
following example YAML template files are provided in the repository as
reference for Kubernetes deployment:
This image can also be deployed on a Kubernetes cluster, such as [minikube](https://kubernetes.io/docs/setup/learning-environment/minikube/).The following example YAML files are provided in the repository as reference for Kubernetes deployment:
* [`machine-learning-ui-deployment.yaml`](https://github.com/clearlinux/dockerfiles/blob/master/machine-learning-ui/machine-learning-ui-deployment.yaml):
example to provide jupyter notebook service.
- [`machine-learning-ui-deployment.yaml`](https://github.com/clearlinux/dockerfiles/blob/master/machine-learning-ui/machine-learning-ui-deployment.yaml): example to provide jupyter notebook service.
To deploy the image on a Kubernetes cluster:
1. Review the contents of the template file and edit appropriately for your needs.
Steps to deploy notebook on a Kubernetes cluster:
2. Deploy machine-learning-ui-deployment.yaml.
```
kubectl create -f machine-learning-ui-deployment.yaml
```
1. Deploy `machine-learning-ui-deployment.yaml`
3. Navigate to http://<nodeip>:30001 in your browser, where 30001 is the port number defined in your service..
```
kubectl create -f machine-learning-ui-deployment.yaml
```
<!-- Required -->
## Build and modify:
2. Navigate to [http://\<nodeIP\>:30001](http://\<nodeIP\>:30001) in your browser, where 30001 is the port number defined in your service.
The Dockerfiles for all Clear Linux* OS based container images are available at
https://github.com/clearlinux/dockerfiles. These can be used to build and
modify the container images.
1. Clone the clearlinux/dockerfiles repository.
```
git clone https://github.com/clearlinux/dockerfiles.git
```
2. Change to the directory of the application:
```
cd machine-learning-ui/
```
3. Build the container image:
```
docker build -t clearlinux/machine-learning-ui .
```
Refer to the Docker documentation for [default build arguments](https://docs.docker.com/engine/reference/builder/#arg).
Additionally:
- `swupd_args` - specifies arguments to pass to the Clear Linux* OS software
manager. See the [swupd man pages](https://github.com/clearlinux/swupd-client/blob/master/docs/swupd.1.rst#options)
for more information.
<!-- Required -->
## Licenses
All licenses for the Clear Linux* Project and distributed software can be found
at https://clearlinux.org/terms-and-policies