Search icon
Subscription
0
Cart icon
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
The Definitive Guide to Google Vertex AI

You're reading from  The Definitive Guide to Google Vertex AI

Product type Book
Published in Dec 2023
Publisher Packt
ISBN-13 9781801815260
Pages 422 pages
Edition 1st Edition
Languages
Authors (2):
Jasmeet Bhatia Jasmeet Bhatia
Profile icon Jasmeet Bhatia
Kartik Chaudhary Kartik Chaudhary
Profile icon Kartik Chaudhary
View More author details

Table of Contents (24) Chapters

Preface 1. Part 1:The Importance of MLOps in a Real-World ML Deployment
2. Chapter 1: Machine Learning Project Life Cycle and Challenges 3. Chapter 2: What Is MLOps, and Why Is It So Important for Every ML Team? 4. Part 2: Machine Learning Tools for Custom Models on Google Cloud
5. Chapter 3: It’s All About Data – Options to Store and Transform ML Datasets 6. Chapter 4: Vertex AI Workbench – a One-Stop Tool for AI/ML Development Needs 7. Chapter 5: No-Code Options for Building ML Models 8. Chapter 6: Low-Code Options for Building ML Models 9. Chapter 7: Training Fully Custom ML Models with Vertex AI 10. Chapter 8: ML Model Explainability 11. Chapter 9: Model Optimizations – Hyperparameter Tuning and NAS 12. Chapter 10: Vertex AI Deployment and Automation Tools – Orchestration through Managed Kubeflow Pipelines 13. Chapter 11: MLOps Governance with Vertex AI 14. Part 3: Prebuilt/Turnkey ML Solutions Available in GCP
15. Chapter 12: Vertex AI – Generative AI Tools 16. Chapter 13: Document AI – An End-to-End Solution for Processing Documents 17. Chapter 14: ML APIs for Vision, NLP, and Speech 18. Part 4: Building Real-World ML Solutions with Google Cloud
19. Chapter 15: Recommender Systems – Predict What Movies a User Would Like to Watch 20. Chapter 16: Vision-Based Defect Detection System – Machines Can See Now! 21. Chapter 17: Natural Language Models – Detecting Fake News Articles! 22. Index 23. Other Books You May Enjoy

Importing data to use with Vertex AI AutoML

The first step when planning to use the Vertex AI AutoML feature is to import the data you plan to use to train as Vertex AI datasets:

  1. Navigate to Vertex AI | Datasets within the Google Cloud console, and click Create to start creating a new Vertex AI dataset.
Figure 5.1 – Creating a Vertex AI dataset

Figure 5.1 – Creating a Vertex AI dataset

  1. Type in the name of the dataset, select Tabular as the data type, choose Regression/classification, and then click CREATE.
Figure 5.2 – Selecting a dataset type and model objective

Figure 5.2 – Selecting a dataset type and model objective

  1. Upload the file named hotel_reservation_data.csv that you previously downloaded from the GitHub repository.

Figure 5.3 – Specifying a data source

  1. Enter a path to the GCS location where you would like to store the imported file. If you have not created a GCS bucket before, click on Browse and type in a name for the storage...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime}