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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.

For help or feedback, please join Metaflow Slack. To suggest an article, you may open an issue on GitHub.

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