Examples

This example folder is dedicated to provide our users with some practical examples.

Here you can find a list with brief descriptions for each example:

• batch_inference: Run a offline batch inference job.
• gan: Tutorial on how to create and train a GAN model with a custom TrainerStep and PreprocessorStep.
• gcp_dataflow_processing: Showcases distributed preprocessing wth Dataflow as the processing backend.
• gcp_gcaip_deployment: Deploying a classifier with Google Cloud AI Platform.
• gcp_gcaip_training: Training a classifier with Google Cloud AI Platform.
• gcp_gpu_orchestrated: Training a classifier on an (optionally preemtible) cuda-enabled Google Cloud Platform virtual machine.
• gcp_kubernetes_orchestrated: Launches a kubernetes job on a kubernetes cluster.
• gcp_orchestrated: Runs pipeline on an (optionally preemtible) virtual machine on Google Cloud Platform as the orchestration backend.
• pytorch: Showcases PyTorch support.
• quickstart: The official quickstart tutorial.

Note: A lot of the examples are based on Google Cloud Platform. Extensions to other cloud providers like AWS and Azure will be released over time, but the interactions will be very similar. In fact, adding support for these can a great first pull request if you would to be a contributor to ZenML!

Have any questions? Want more tutorials? Spot out-dated, frustrating tutorials? We got you covered!

Feel free to let us know by creating an issue here on our Github or by reaching out to us on our Slack.