Course Overview
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 re-trained models as part of your machine learning workflow and how to fine-tune models for your specific applications.
Quem deve participar
Machine learning practitioners who wish to leverage models available in Vertex AI Model Garden for various different use cases.
Pré- requisitos
To get the most out of this course, participants should have:
- Prior completion of Machine Learning on Google Cloud (MLGC) 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.
Objetivos do Curso
- Understanding 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