Vertex AI Model Garden

Vertex AI Model Garden provides enterprise-ready foundation models, task-specific models, and APIs. Model Garden can serve as the starting point for model discovery for various different use cases. You can kick off a variety of workflows including using models directly, tuning models in Generative AI Studio, or deploying models to a data science notebook. In this class, after being introduced to Vertex AI as a machine learning platform through the lens of Model Garden. You will learn how to leverage pre-trained models as part of your machine learning workflow and how to fine-tune models for your specific applications.


Neste curso, os participantes aprenderão as seguintes habilidades:

  • Understand the model options available within Vertex AI Model Garden
  • Incorporate models in Vertex AI Model Garden in your machine learning workflows
  • Leverage foundation models for generative AI use cases
  • Fine-tune models to meet your specific needs


Esta aula destina-se ao seguinte público:

  • Machine learning practitioners who wish to leverage models available in Vertex AI Model Garden for various different use cases.


Para aproveitar ao máximo este curso, os participantes precisam atender aos seguintes critérios:
  • Prior completion Machine Learning on Google Cloud course or the equivalent knowledge of TensorFlow/Keras and machine learning.
  • Experience scripting in Python and working in Jupyter notebooks to create machine learning models.


1 dia


Caso tenha interesse em uma turma para sua empresa, por favor entre em contato conosco.

Resumo do curso

1 day of introductory to intermediate-level training for machine learning practitioners to get started with Vertex AI Model Garden This class includes lecture, demonstrations and hands-on lab activities.

  • Vertex AI on Google Cloud
  • Options for training, tuning and deploying ML models on Vertex AI
  • Generative AI options on Google Cloud and Vertex AI
  • Introduction to Model Garden
  • Model types in Model Garden
  • Connecting models from Gen AI Studio and Model Registry
  • Introduction to course use cases
  • Pre-trained models for specific tasks
  • VertexAI AutoML
  • Using a pre-trained model via the Python SDK
  • Lab: Content Classification via Natural Language API and AutoML
  • Introduction to foundation models
  • PaLM API
  • GenAI Studio
  • Using the Embeddings API
  • Lab: Use the PaLM API to Cluster Products Based on Descriptions
  • Fine-tunable models in Model Garden
  • Vertex AI Pipelines
  • Demo: Fine-tuning models for your specific use case