Introduction to Metaflow Tutorial | Outerbounds (original) (raw)

In this tutorial you will learn how to write scalable, production-ready data science and machine learning code. By following along, you will implement a variety of patterns to help you build a machine learning stack to handle data, access compute, faciltate robust versioning, and more. At the end of this tutorial you will be able to:

• Design basic machine learning workflows.
• Version and track data in your machine learning systems.
• Train and track models in parallel.

from metaflow import FlowSpec, step

class MinimumFlow(FlowSpec):
    
    @step
    def start(self):
        self.next(self.end)
    
    @step
    def end(self):
        print("Flow is done!")

if __name__ == "__main__":
    MinimumFlow()

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