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ML Engineering on Google Cloud Platform

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This repository maintains hands-on labs and code samples that demonstrate best practices and patterns for implementing and operationalizing production grade machine learning workflows on Google Cloud Platform.

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This repository is organized into two sections:

Mini workshops

This section contains hands-on labs for instructor led ML Engineering mini workshops.

Code Samples

This section compiles samples demonstrating design and code patterns for a variety of ML Engineering topics.

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  • Jupyter Notebook 84.0%
  • Python 15.3%
  • Shell 0.4%
  • Dockerfile 0.2%
  • HCL 0.1%
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