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Launching into Machine Learning

Launching into Machine Learning

magic_button Machine Learning Pipeline Machine Learning Machine Learning Models
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32 hours Introductory universal_currency_alt 20 Credits

The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.

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Course Info
Objectives
  • Describe how to improve data quality and perform exploratory data analysis
  • Build and train AutoML Models using Vertex AI and BigQuery ML
  • Optimize and evaluate models using loss functions and performance metrics
  • Create repeatable and scalable training, evaluation, and test datasets
Prerequisites
Familiarity with Python or other programming languages
Audience
  • Aspiring machine learning data scientists and engineers
  • Machine learning scientists, data scientists, and data analysts
  • Data engineers
Available languages
English, español (Latinoamérica), 日本語, français, 한국어 ve português (Brasil)
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