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12

Machine Learning Operations (MLOps) with Vertex AI: Manage Features

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12

Machine Learning Operations (MLOps) with Vertex AI: Manage Features

magic_button Machine Learning Pipeline Machine Learning Operations Machine Learning
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8 hours Intermediate universal_currency_alt 5 Credits

This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production.

Learners will get hands-on practice using Vertex AI Feature Store's streaming ingestion at the SDK layer.

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Course Info
Objectives
  • Containerize ML workflows for reproducibility, reuse, and scalable training and inference on Google Cloud.
  • Efficiently share, discover, and re-use ML features at scale while conducting reproducible ML experiments with Vertex AI Feature Store.
Prerequisites
  • Proficiency with Python on topics covered in the Crash Course on Python.
  • Prior experience with foundational machine learning concepts and building machine learning solutions on Google Cloud as covered in the Machine Learning on Google Cloud course.
Audience
Intermediate
Available languages
English ، español (Latinoamérica) ، français ، 日本語 ، 한국어 و português (Brasil)
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