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.

    Objectives

    In this course, participants will learn the following skills:

    • 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

    Audience

    This course is intended for the following participants:

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

    Prerequisites

    Basic understanding of one or more of the following:

    • 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

    Duration

    1 day

    Investment

    Check the next open public class in our enrollment page.
    If you are interested in a private training class for your company, contact us.

    Course Outline

    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
    Check our schedule and enroll