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Jupyter Notebooks on GCP (Development Best Practices/Tooling)

Technical talk | English

Track 4 - Theatre 15

Thursday - 12.25 to 13.05 - Technical

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The Jupyter Notebook is an invaluable tool for quick prototyping and development, but lacks the best practices and processes common to software engineering. In this talk, we will showcase how to integrate these generally omitted best practices to convert your notebooks into fully reproducible, production-ready artifacts. First, we will start by creating a self-contained notebook on a local laptop. Then, by leveraging Google Cloud Platform’s Deep Learning Environment, we will showcase how this notebook, without modification, can be submitted to GCP for background execution, or transferred to AI Platform Notebooks for continued editing. Finally, we will demonstrate how to automate the creation of derivative artifacts from the notebook using a CI/CD pipeline.

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