Course Outline


Overview of AutoML Features and Architecture

  • Google’s ML ecosystem
  • AutoML line of products

Working With Google’s Machine Learning Ecosystem

  • Applications for AutoML products
  • Challenges and limitations

Evaluating Content Using AutoML Natural Language

  • Preparing datasets
  • Creating and deploying models
  • Text and document training (classification, extraction, analysis)

Classifying Images Using AutoML Vision

  • Labeling images
  • Training and evaluating models
  • AutoML Vision Edge

Creating Translation Models Using AutoML Translation

  • Preparing datasets (source and target language)
  • Creating and managing models
  • Testing models

Making Predictions from Trained Models

  • Analyzing documents
  • Image prediction
  • Translating content

Exploring Other AutoML Products

  • AutoML Tables for structured data
  • AutoML Video Intelligence for videos


Summary and Conclusion


  • Basic knowledge of data analytics
  • Familiarity with machine learning


  • Data scientists
  • Data analysts
  • Developers
  7 Hours

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