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.
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What you’ll learn
This course teaches participants 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
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Lumify Work is Australia's only national Google Cloud Authorised Training Partner. Get the skills needed to build, test, and deploy applications on this highly scalable infrastructure. Engineered to handle the most data-intensive work you can throw at it, Lumify Work can support you through training wherever you are in your Cloud adoption journey.
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Don’t let your tech outpace the skills of your people
Train Anywhere
From our state-of-the-art classrooms to telepresence to your offices, our instructor-led training caters to your needs.
Track Record
We have a 30-year history of driving innovative, award-winning learning solutions.
More Courses, More Often
When you train with Lumify Work you get more courses, more often, in more locations, and from more vendors.
Quality Instructors and Content
Expert instructors with real world experience and the latest vendor-approved in-depth course content.
Partner-Preferred Supplier
Chosen and awarded by the world's leading vendors as preferred training partner.
Ahead of the Technology Curve
No matter your chosen technologies or platforms, we can help you stay one step ahead.
Train Anywhere
From our state-of-the-art classrooms to telepresence to your offices, our instructor-led training caters to your needs.
Track Record
We have a 30-year history of driving innovative, award-winning learning solutions.
More Courses, More Often
When you train with Lumify Work you get more courses, more often, in more locations, and from more vendors.
Quality Instructors and Content
Expert instructors with real world experience and the latest vendor-approved in-depth course content.
Partner-Preferred Supplier
Chosen and awarded by the world's leading vendors as preferred training partner.
Ahead of the Technology Curve
No matter your chosen technologies or platforms, we can help you stay one step ahead.
Train Anywhere
From our state-of-the-art classrooms to telepresence to your offices, our instructor-led training caters to your needs.
Track Record
We have a 30-year history of driving innovative, award-winning learning solutions.
More Courses, More Often
When you train with Lumify Work you get more courses, more often, in more locations, and from more vendors.
Who is the course for?
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.
Course subjects
Module 1: Vertex AI for ML Workloads
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
Module 2: Model Garden
Introduction to Model Garden
Model types in Model Garden
Connecting models from Gen AI Studio and Model Registry
Lab: Content Classification via Natural Language API and AutoML
Module 4: Foundation Models: Text Embeddings via PaLM
Introduction to foundation models
PaLM API
GenAI Studio
Using the Embeddings API
Lab: Use the PaLM API to Cluster Products Based on Descriptions
Module 5: Fine-tunable Models
Fine-tunable models in Model Garden
Vertex AI Pipelines
Demo: Fine-tuning models for your specific use case
Prerequisites
To get the most out of this course, participants should have:
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.
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Terms & Conditions
The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.
Request Course Information
By submitting an enquiry, you agree to our privacy policy and receiving email and other forms of communication from us. You can opt-out at any time.
