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Learning Google Cloud Vertex Ai

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The Definitive Guide To Google Vertex Ai

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Author : Jasmeet Bhatia
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-12-29

The Definitive Guide To Google Vertex Ai written by Jasmeet Bhatia and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-29 with Computers categories.

Implement machine learning pipelines with Google Cloud Vertex AI Key Features Understand the role of an AI platform and MLOps practices in machine learning projects Get acquainted with Google Vertex AI tools and offerings that help accelerate the creation of end-to-end ML solutions Implement Vision, NLP, and recommendation-based real-world ML models on Google Cloud Platform Purchase of the print or Kindle book includes a free PDF eBook Book 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 learn Understand the ML lifecycle, challenges, and importance of MLOps Get started with ML model development quickly using Google Vertex AI Manage datasets, artifacts, and experiments Develop no-code, low-code, and custom AI solution on Google Cloud Implement advanced model optimization techniques and tooling Understand pre-built and turnkey AI solution offerings from Google Build and deploy custom ML models for real-world applications Explore the latest generative AI tools within Vertex AI Who this book is for If 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.

Learning Google Cloud Vertex Ai

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Author : Hemanth Kumar K
language : en
Publisher: BPB Publications
Release Date : 2023-08-28

Learning Google Cloud Vertex Ai written by Hemanth Kumar K and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-28 with Computers categories.

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

Learning Google Cloud Vertex Ai

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Author : Hemanth Kumar K
language : en
Publisher: BPB Publications
Release Date : 2023-08-28

Learn Vertex Ai

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Author : Diego Rodrigues
language : en
Publisher: StudioD21
Release Date : 2025-06-27

Learn Vertex Ai written by Diego Rodrigues and has been published by StudioD21 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-27 with Business & Economics categories.

LEARN VERTEX AI Implement Enterprise AI on Google Cloud This book is aimed at technology professionals, data engineers, and students who want to master the use of Vertex AI for creating, automating, and governing artificial intelligence projects in corporate Google Cloud environments. Learn how to structure machine learning pipelines, integrate data, automate deployment and versioning processes, monitor performance, and implement MLOps and DataOps practices with security, scalability, and compliance. Explore practical integrations with BigQuery, Dataflow, Pub/Sub, Cloud Storage, as well as leading frameworks such as TensorFlow, PyTorch, and scikit-learn. Develop skills in multi-cloud deployment, model tuning, cost control, CI/CD automation, and complete governance of the data and model lifecycle. • Professional setup of Vertex AI on Google Cloud • Building automated and scalable machine learning pipelines • Advanced integration with BigQuery, Dataflow, Pub/Sub, and Cloud Storage • Deployment, versioning, and monitoring of production models • Orchestration with TensorFlow, PyTorch, scikit-learn, AutoML, and containers • CI/CD automation, performance tuning, cost control • Implementation of Feature Store, Model Registry, and access policies • Governance, auditing, compliance, and data security in AI • MLOps, DataOps strategies, and multi-cloud integration • Real-world applications, certification preparation, and critical projects Master Vertex AI and become a reference in corporate AI, delivering scalable, auditable projects aligned with global market demands. vertex ai, google cloud, machine learning, nvidia, pipelines, automation, bigquery, dataflow, pub/sub, cloud storage, ci/cd, mlops, automl, tensorflow, pytorch, feature store, model registry, dataops, model deployment, orchestration, monitoring, governance, data security

Generative Ai On Google Cloud With Langchain

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Author : Leonid Kuligin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-12-20

Generative Ai On Google Cloud With Langchain written by Leonid Kuligin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-20 with Computers categories.

Turn challenges into opportunities by mastering advanced techniques for text generation, summarization, and question answering using LangChain and Google Cloud tools Key Features Solve real-world business problems with hands-on examples of GenAI applications on Google Cloud Learn repeatable design patterns for Gen AI on Google Cloud with a focus on architecture and AI ethics Build and implement GenAI agents and workflows, such as RAG and NL2SQL, using LangChain and Vertex AI Purchase of the print or Kindle book includes a free PDF eBook Book Description The rapid transformation and enterprise adoption of GenAI has created an urgent demand for developers to quickly build and deploy AI applications that deliver real value. Written by three distinguished Google AI engineers and LangChain contributors who have shaped Google Cloud’s integration with LangChain and implemented AI solutions for Fortune 500 companies, this book bridges the gap between concept and implementation, exploring LangChain and Google Cloud’s enterprise-ready tools for scalable AI solutions. You'll start by exploring the fundamentals of large language models (LLMs) and how LangChain simplifies the development of AI workflows by connecting LLMs with external data and services. This book guides you through using essential tools like the Gemini and PaLM 2 APIs, Vertex AI, and Vertex AI Search to create sophisticated, production-ready GenAI applications. You'll also overcome the context limitations of LLMs by mastering advanced techniques like Retrieval-Augmented Generation (RAG) and external memory layers. Through practical patterns and real-world examples, you’ll gain everything you need to harness Google Cloud’s AI ecosystem, reducing the time to market while ensuring enterprise scalability. You’ll have the expertise to build robust GenAI applications that can be tailored to solve real-world business challenges. What you will learn Build enterprise-ready applications with LangChain and Google Cloud Navigate and select the right Google Cloud generative AI tools Apply modern design patterns for generative AI applications Plan and execute proof-of-concepts for enterprise AI solutions Gain hands-on experience with LangChain's and Google Cloud's AI products Implement advanced techniques for text generation and summarization Leverage Vertex AI Search and other tools for scalable AI solutions Who this book is for If you’re an application developer or ML engineer eager to dive into GenAI, this book is for you. Whether you're new to LangChain or Google Cloud, you'll learn how to use these tools to build scalable AI solutions. This book is ideal for developers familiar with Python and machine learning basics looking to apply their skills in GenAI. Professionals who want to explore Google Cloud's powerful suite of enterprise-grade GenAI products and their implementation will also find this book useful.

Journey To Become A Google Cloud Machine Learning Engineer

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Author : Dr. Logan Song
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-09-20

Journey To Become A Google Cloud Machine Learning Engineer written by Dr. Logan Song and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-20 with Computers categories.

Prepare for the GCP ML certification exam along with exploring cloud computing and machine learning concepts and gaining Google Cloud ML skills Key FeaturesA comprehensive yet easy-to-follow Google Cloud machine learning study guideExplore full-spectrum and step-by-step practice examples to develop hands-on skillsRead through and learn from in-depth discussions of Google ML certification exam questionsBook Description This book aims to provide a study guide to learn and master machine learning in Google Cloud: to build a broad and strong knowledge base, train hands-on skills, and get certified as a Google Cloud Machine Learning Engineer. The book is for someone who has the basic Google Cloud Platform (GCP) knowledge and skills, and basic Python programming skills, and wants to learn machine learning in GCP to take their next step toward becoming a Google Cloud Certified Machine Learning professional. The book starts by laying the foundations of Google Cloud Platform and Python programming, followed the by building blocks of machine learning, then focusing on machine learning in Google Cloud, and finally ends the studying for the Google Cloud Machine Learning certification by integrating all the knowledge and skills together. The book is based on the graduate courses the author has been teaching at the University of Texas at Dallas. When going through the chapters, the reader is expected to study the concepts, complete the exercises, understand and practice the labs in the appendices, and study each exam question thoroughly. Then, at the end of the learning journey, you can expect to harvest the knowledge, skills, and a certificate. What you will learnProvision Google Cloud services related to data science and machine learningProgram with the Python programming language and data science librariesUnderstand machine learning concepts and model development processesExplore deep learning concepts and neural networksBuild, train, and deploy ML models with Google BigQuery ML, Keras, and Google Cloud Vertex AIDiscover the Google Cloud ML Application Programming Interface (API)Prepare to achieve Google Cloud Professional Machine Learning Engineer certificationWho this book is for Anyone from the cloud computing, data analytics, and machine learning domains, such as cloud engineers, data scientists, data engineers, ML practitioners, and engineers, will be able to acquire the knowledge and skills and achieve the Google Cloud professional ML Engineer certification with this study guide. Basic knowledge of Google Cloud Platform and Python programming is required to get the most out of this book.

Official Google Cloud Certified Professional Machine Learning Engineer Study Guide

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Author : Mona Mona
language : en
Publisher: John Wiley & Sons
Release Date : 2023-10-27

Official Google Cloud Certified Professional Machine Learning Engineer Study Guide written by Mona Mona and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-27 with Computers categories.

Expert, guidance for the Google Cloud Machine Learning certification exam In Google Cloud Certified Professional Machine Learning Study Guide, a team of accomplished artificial intelligence (AI) and machine learning (ML) specialists delivers an expert roadmap to AI and ML on the Google Cloud Platform based on new exam curriculum. With Sybex, you’ll prepare faster and smarter for the Google Cloud Certified Professional Machine Learning Engineer exam and get ready to hit the ground running on your first day at your new job as an ML engineer. The book walks readers through the machine learning process from start to finish, starting with data, feature engineering, model training, and deployment on Google Cloud. It also discusses best practices on when to pick a custom model vs AutoML or pretrained models with Vertex AI platform. All technologies such as Tensorflow, Kubeflow, and Vertex AI are presented by way of real-world scenarios to help you apply the theory to practical examples and show you how IT professionals design, build, and operate secure ML cloud environments. The book also shows you how to: Frame ML problems and architect ML solutions from scratch Banish test anxiety by verifying and checking your progress with built-in self-assessments and other practical tools Use the Sybex online practice environment, complete with practice questions and explanations, a glossary, objective maps, and flash cards A can’t-miss resource for everyone preparing for the Google Cloud Certified Professional Machine Learning certification exam, or for a new career in ML powered by the Google Cloud Platform, this Sybex Study Guide has everything you need to take the next step in your career.

Google Cloud Developer Certification

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Author : Cybellium
language : en
Publisher: Cybellium Ltd
Release Date : 2024-10-26

Google Cloud Developer Certification written by Cybellium and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-26 with Computers categories.

Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com

Responsible Ai In The Enterprise

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Author : Adnan Masood
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-07-31

Responsible Ai In The Enterprise written by Adnan Masood and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-31 with Computers categories.

Build and deploy your AI models successfully by exploring model governance, fairness, bias, and potential pitfalls Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn ethical AI principles, frameworks, and governance Understand the concepts of fairness assessment and bias mitigation Introduce explainable AI and transparency in your machine learning models Book DescriptionResponsible AI in the Enterprise is a comprehensive guide to implementing ethical, transparent, and compliant AI systems in an organization. With a focus on understanding key concepts of machine learning models, this book equips you with techniques and algorithms to tackle complex issues such as bias, fairness, and model governance. Throughout the book, you’ll gain an understanding of FairLearn and InterpretML, along with Google What-If Tool, ML Fairness Gym, IBM AI 360 Fairness tool, and Aequitas. You’ll uncover various aspects of responsible AI, including model interpretability, monitoring and management of model drift, and compliance recommendations. You’ll gain practical insights into using AI governance tools to ensure fairness, bias mitigation, explainability, privacy compliance, and privacy in an enterprise setting. Additionally, you’ll explore interpretability toolkits and fairness measures offered by major cloud AI providers like IBM, Amazon, Google, and Microsoft, while discovering how to use FairLearn for fairness assessment and bias mitigation. You’ll also learn to build explainable models using global and local feature summary, local surrogate model, Shapley values, anchors, and counterfactual explanations. By the end of this book, you’ll be well-equipped with tools and techniques to create transparent and accountable machine learning models.What you will learn Understand explainable AI fundamentals, underlying methods, and techniques Explore model governance, including building explainable, auditable, and interpretable machine learning models Use partial dependence plot, global feature summary, individual condition expectation, and feature interaction Build explainable models with global and local feature summary, and influence functions in practice Design and build explainable machine learning pipelines with transparency Discover Microsoft FairLearn and marketplace for different open-source explainable AI tools and cloud platforms Who this book is for This book is for data scientists, machine learning engineers, AI practitioners, IT professionals, business stakeholders, and AI ethicists who are responsible for implementing AI models in their organizations.

Google Cloud Architect Handbook

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Author : Ajay Kumar
language : en
Publisher: BPB Publications
Release Date : 2025-02-04

Google Cloud Architect Handbook written by Ajay Kumar and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-04 with Computers categories.

DESCRIPTION Become a master of Google Cloud Platform (GCP) and design, deploy, and manage cutting-edge cloud solutions with confidence. This book is your key to unlocking the full potential of GCP, from mastering key services to architecting for high availability, disaster recovery, and optimal performance. This book is a complete guide to GCP, covering core services like Compute Engine, Kubernetes Engine, and App Engine for running applications. It explores storage solutions such as Cloud Storage, Cloud SQL, and Bigtable, and dives into data analytics with BigQuery and ML tools like Vertex AI and AutoML. Networking topics include VPCs, subnets, and load balancing, while security best practices like IAM and data encryption are highlighted. The book also emphasizes DevOps practices, CI/CD, and Infrastructure as Code (IaC), alongside strategies for building reliable systems with high availability and disaster recovery. It concludes with tips for the GCP Professional Cloud Architect certification, making it a valuable resource for mastering GCP. Through real-world case studies and expert insights, you will gain a practical understanding of how to design and deploy applications that meet the demands of modern businesses. Discover how to navigate complex challenges, optimize performance, and ensure your solutions are secure, resilient, and cost-effective. KEY FEATURES ● Master GCP's core services, from computing and storage to networking, databases, and big data analytics. ● Design scalable, reliable systems with disaster recovery plans and performance for demanding applications. ● Explore real-world case studies and discover best practices for security, cost optimization, and efficient cloud management. WHAT YOU WILL LEARN ● Develop scalable, high-availability solutions for handling traffic surges. ● Strengthen security for data, apps, and infrastructure against threats. ● Leverage BigQuery and analytics tools for data-driven insights. ● Master Kubernetes and Deployment Manager for smooth application delivery. ● Gain the knowledge and skills needed to succeed in the Google Cloud Professional Cloud Architect certification exam. WHO THIS BOOK IS FOR This book is for experienced and aspiring cloud professionals, including IT specialists, developers, and architects, who want to design, build, and manage solutions on GCP. TABLE OF CONTENTS 1. Introduction to Google Cloud Platform 2. Getting Started with GCP 3. Compute and Storage 4. Data and Analytics 5. Machine Learning and AI Services 6. Networking in GCP 7. Identity and Access Management 8. Security and Compliance 9. DevOps and Site Reliability Engineering 10. High Availability and Disaster Recovery 11. Logging, Monitoring and Troubleshooting 12. Hybrid and Multi Cloud Strategies 13. Exam Preparation and Tips

Learning Google Cloud Vertex Ai

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