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Introduction to Metaflow Tutorial

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.
Your First Flow

Try it out directly in your browser

Open in Sandbox
from metaflow import FlowSpec, step

class MinimumFlow(FlowSpec):

def start(self):

def end(self):
print("Flow is done!")

if __name__ == "__main__":