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### Building
Start with building your *<%= engine_name %>* engine. Run the following command:
```
$ pio build --verbose
```
This command should take few minutes for the first time; all subsequent builds
should be less than a minute. You can also run it without `--verbose` if you don't want to see all the log messages.
Upon successful build, you should see a console message similar to the
following.
```
[INFO] [Console$] Your engine is ready for training.
```
### Training the Predictive Model
To train your engine, run the following command:
```
$ pio train
```
When your engine is trained successfully, you should see a console message
similar to the following.
```
[INFO] [CoreWorkflow$] Training completed successfully.
```
### Deploying the Engine
Now your engine is ready to deploy. Run:
```
$ pio deploy
```
When the engine is deployed successfully and running, you should see a console message similar to the following:
```
[INFO] [HttpListener] Bound to /0.0.0.0:8000
[INFO] [MasterActor] Bind successful. Ready to serve.
```
Do not kill the deployed engine process.
By default, the deployed engine binds to http://localhost:8000. You can visit
that page in your web browser to check its status.
![Engine Status](/images/engine-server.png)