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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, and português (Brasil)
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View the public classroom schedule here.
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