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Machine Learning in the Enterprise

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Machine Learning in the Enterprise

magic_button Machine Learning Models Machine Learning Model Training Machine Learning
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32 heures Débutant universal_currency_alt 22 crédits

This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing.

The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.

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Informations sur le cours
Objectifs
  • Describe data management, governance, and preprocessing options.
  • Identify when to use Vertex AutoML, BigQuery ML, and custom training.
  • Implement Vertex Vizier Hyperparameter Tuning.
  • Explain how to create batch and online predictions, setup model monitoring, and create pipelines using Vertex AI.
Prérequis
Some familiarity with basic machine learning concepts Basic proficiency with a scripting language; Python preferred
Cible
  • Data Analysts
  • Data Engineers
  • Data Scientists
  • ML Engineers
  • ML Software Engineers
Langues disponibles
English, español (Latinoamérica), 日本語, français, 한국어 et português (Brasil)
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