The Definitive Guide to Google Vertex AI: Accelerate your machine learning journey with Google Cloud Vertex AI and MLOps best practices

Implement machine learning pipelines with Google Cloud Vertex AIKey FeaturesUnderstand the role of an AI platform and MLOps practices in machine learning projectsGet acquainted with Google Vertex AI tools and offerings that help accelerate the creation of end-to-end ML solutionsImplement Vision, NLP, and recommendation-based real-world ML models on Google Cloud PlatformPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionWhile AI has become an integral part of every organization today, the development of large-scale ML solutions and management of complex ML workflows in production continue to pose challenges for many. Google’s unified data and AI platform, Vertex AI, directly addresses these challenges with its array of MLOPs tools designed for overall workflow management.This book is a comprehensive guide that lets you explore Google Vertex AI’s easy-to-advanced level features for end-to-end ML solution development. Throughout this book, you’ll discover how Vertex AI empowers you by providing essential tools for critical tasks, including data management, model building, large-scale experimentations, metadata logging, model deployments, and monitoring. You’ll learn how to harness the full potential of Vertex AI for developing and deploying no-code, low-code, or fully customized ML solutions. This book takes a hands-on approach to developing u deploying some real-world ML solutions on Google Cloud, leveraging key technologies such as Vision, NLP, generative AI, and recommendation systems. Additionally, this book covers pre-built and turnkey solution offerings as well as guidance on seamlessly integrating them into your ML workflows.By the end of this book, you’ll have the confidence to develop and deploy large-scale production-grade ML solutions using the MLOps tooling and best practices from Google.What you will learnUnderstand the ML lifecycle, challenges, and importance of MLOpsGet started with ML model development quickly using Google Vertex AIManage datasets, artifacts, and experimentsDevelop no-code, low-code, and custom AI solution on Google CloudImplement advanced model optimization techniques and toolingUnderstand pre-built and turnkey AI solution offerings from GoogleBuild and deploy custom ML models for real-world applicationsExplore the latest generative AI tools within Vertex AIWho this book is forIf you are a machine learning practitioner who wants to learn end-to-end ML solution development on Google Cloud Platform using MLOps best practices and tools offered by Google Vertex AI, this is the book for you.Table of ContentsMachine Learning project lifecycle and challengesWhat is ML Ops and why is it important for every organization using ML?It's all about Data - Options to store and transform ML datasetsVertex AI Workbench - One stop tool for all your ML Development needsTraining ML Models - No code option - AutoMLTraining ML Models -Low code option - BQMLTraining fully custom ML models with Vertex AIModel Explainability through Vertex AIModel optimizations – Hyper parameter tuning and NAS (TBD)Vertex AI Deployment and Automation tools – Orchestration through managed Kubeflow pipelinesVertex AI Governance ToolsVertex AI - Generative AI ToolsDocument AI – Customizable document processing solutionML APIs – Vision API, NLP API etc.Recommender Systems - Predict what movie would you like to watch?(N.B. Please use the Look Inside option to see further chapters) Read more