Learn how to build an end-to-end data to AI solution on Google Cloud using Vertex AI Key Features ? Harness the power of AutoML capabilities to build machine learning models. ? Learn how to train custom machine learning models on the Google Cloud Platform. ? Accelerate your career in data analytics by leveraging the capabilities of GCP. Description Google Cloud Vertex AI is a platform for machine learning (ML) offered by Google Cloud, with the objective of making the creation, deployment, and administration of ML models on a large scale easier. If you are seeking a unified and collaborative environment for your ML projects, this book is a valuable resource for you. This comprehensive guide is designed to help data enthusiasts effectively utilize Google Cloud Platform's Vertex AI for a wide range of machine learning operations. It covers the basics of the Google Cloud Platform, encompassing cloud storage, big query, and IAM. Subsequently, it delves into the specifics of Vertex AI, including AutoML, custom model training, model deployment on endpoints, development of Vertex AI pipelines, and the Explainable AI feature store. By the time you finish reading this book, you will be able to navigate Vertex AI proficiently, even if you lack prior experience with cloud platforms. With the inclusion of numerous code examples throughout the book, you will be equipped with the necessary skills and confidence to create machine learning solutions using Vertex AI. What you will learn ? Learn how to create projects, store data in GCP, and manage access permissions effectively. ? Discover how AutoML can be utilized for streamlining workflows. ? Learn how to construct pipelines using TFX (TensorFlow Extended) and Kubeflow components. ? Gain an overview of the purpose and significance of the Feature Store. ? Explore the concept of explainable AI and its role in understanding machine learning models. Who this book is for This book is designed for data scientists and advanced AI practitioners who are interested in learning how to perform machine learning tasks on the Google Cloud Platform. Having prior knowledge of machine learning concepts and proficiency in Python programming would greatly benefit readers. Table of Contents 1. Basics of Google Cloud Platform 2. Introduction to Vertex AI and AutoML Tabular 3. AutoML Image, Text, and Pre-built Models 4. Vertex AI Workbench and Custom Model Training 5. Vertex AI Custom Model Hyperparameter and Deployment 6. Introduction to Pipelines and Kubeflow 7. Pipelines using Kubeflow for Custom Models 8. Pipelines using TensorFlow Extended 9. Vertex AI Feature Store 10. Explainable AI