Learn how to design machine learning solutions with Google Cloud Platform.
Overview
Syllabus
Introduction
- GCP and Machine Learning
- What you should know
- About using cloud services
- Use Vertex AI Model Garden
- Design and test language model prompts
- Design and test multimodal model prompts
- Test image model generative output
- Design and test speech generative output
- Challenge: Select and test GenAI models
- Solution: Select and test GenAI models
- Understand available services
- Use TensorFlow example: MNIST
- Use managed and user-managed notebooks
- Update notebook instance
- Use notebook instances
- Challenge: Setup notebook
- Solution: Setup notebook
- Understand Vector Search
- Use Vector Search
- Understand Feature Store
- Challenge: Create a Feature Store
- Solution: Create a Feature Store
- Use the model registry
- Register a model in the registry
- Review batch and online endpoints
- Understand model pipeline templates
- Challenge: Run and evaluate a model pipeline job
- Solution: Run and evaluate a model pipeline job
- Next steps
Taught by
Lynn Langit