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

What is Document AI?

Document AI is an end-to-end AI-based solution for extracting and classifying useful information from any kind of unstructured documents, including scanned images, PDFs, forms, emails, and contracts. Document AI’s solution includes pre-trained ML models for extraction and other document-related tasks, and it also provides the flexibility to uptrain existing models and train custom models without writing much code. Document AI is one unified solution that can help businesses manage the entire unstructured document life cycle, ensuring a high level of accuracy and low costs to accelerate deployment to meet customer expectations.

Some key features of Google Cloud’s Document AI platform are as follows:

  • Google’s state-of-the-art AI: The Document AI platform is built upon Google’s industry-leading AI innovations in various fields, including computer vision (including OCR), NLP, and semantic search, to make this platform highly accurate...
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