The Definitive Guide to Google Vertex AI

The Definitive Guide to Google Vertex AI

Author: Jasmeet Bhatia

Publisher: Packt Publishing Ltd

Published: 2023-12-29

Total Pages: 422

ISBN-13: 1801813329

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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.


The Definitive Guide to Google Vertex AI

The Definitive Guide to Google Vertex AI

Author: Jasmeet Bhatia

Publisher: Packt Publishing Ltd

Published: 2023-12-29

Total Pages: 422

ISBN-13: 1801813329

DOWNLOAD EBOOK

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.


Google Machine Learning and Generative AI for Solutions Architects

Google Machine Learning and Generative AI for Solutions Architects

Author: Kieran Kavanagh

Publisher: Packt Publishing Ltd

Published: 2024-06-28

Total Pages: 552

ISBN-13: 1803247029

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Architect and run real-world AI/ML solutions at scale on Google Cloud, and discover best practices to address common industry challenges effectively Key Features Understand key concepts, from fundamentals through to complex topics, via a methodical approach Build real-world end-to-end MLOps solutions and generative AI applications on Google Cloud Get your hands on a code repository with over 20 hands-on projects for all stages of the ML model development lifecycle Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMost companies today are incorporating AI/ML into their businesses. Building and running apps utilizing AI/ML effectively is tough. This book, authored by a principal architect with about two decades of industry experience, who has led cross-functional teams to design, plan, implement, and govern enterprise cloud strategies, shows you exactly how to design and run AI/ML workloads successfully using years of experience from some of the world’s leading tech companies. You’ll get a clear understanding of essential fundamental AI/ML concepts, before moving on to complex topics with the help of examples and hands-on activities. This will help you explore advanced, cutting-edge AI/ML applications that address real-world use cases in today’s market. You’ll recognize the common challenges that companies face when implementing AI/ML workloads, and discover industry-proven best practices to overcome these. The chapters also teach you about the vast AI/ML landscape on Google Cloud and how to implement all the steps needed in a typical AI/ML project. You’ll use services such as BigQuery to prepare data; Vertex AI to train, deploy, monitor, and scale models in production; as well as MLOps to automate the entire process. By the end of this book, you will be able to unlock the full potential of Google Cloud's AI/ML offerings.What you will learn Build solutions with open-source offerings on Google Cloud, such as TensorFlow, PyTorch, and Spark Source, understand, and prepare data for ML workloads Build, train, and deploy ML models on Google Cloud Create an effective MLOps strategy and implement MLOps workloads on Google Cloud Discover common challenges in typical AI/ML projects and get solutions from experts Explore vector databases and their importance in Generative AI applications Uncover new Gen AI patterns such as Retrieval Augmented Generation (RAG), agents, and agentic workflows Who this book is for This book is for aspiring solutions architects looking to design and implement AI/ML solutions on Google Cloud. Although this book is suitable for both beginners and experienced practitioners, basic knowledge of Python and ML concepts is required. The book focuses on how AI/ML is used in the real world on Google Cloud. It briefly covers the basics at the beginning to establish a baseline for you, but it does not go into depth on the underlying mathematical concepts that are readily available in academic material.


No-Code Artificial Intelligence

No-Code Artificial Intelligence

Author: Ambuj Agrawal

Publisher: BPB Publications

Published: 2023-03-07

Total Pages: 280

ISBN-13: 9355513496

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A practical guide that will help you build AI and ML solutions faster with fewer efforts and no programming knowledge KEY FEATURES ● Start your journey to become an AI expert today. ● Learn how to build AI solutions to solve complex problems in your organization. ● Get familiar with different No-code AI tools and platforms. DESCRIPTION “No-Code Artificial Intelligence” is a book that enables you to develop AI applications without any programming knowledge. Authored by the founder of AICromo (https://aicromo.com/), this book takes you through an array of examples that shows how to build AI solutions using No-code AI tools. The book starts by sharing insights on the evolution of No-code AI and the different types of No-code AI tools and platforms available in the market. The book then helps you start building applications of Machine Learning in Finance, Healthcare, Sales, and Cybersecurity. It will also teach you to create AI applications to perform sales forecasting, find fraudulent claims, and detect diseases in plants. Furthermore, the book will show how to build Machine Learning models for a variety of use cases in image recognition, video object recognition, and data prediction. After reading this book, you will be able to build AI applications with ease. WHAT YOU WILL LEARN ● Use different No-code AI tools such as AWS Sagemaker, DataRobot, and Google AutoML. ● Learn how to create a Machine Learning model to predict housing prices. ● Build Natural Language Processing (NLP) models for Healthcare information Identification. ● Learn how to build an AI model to create targeted customer offerings. ● Use traditional ways to perform AI implementation using programming languages and AI libraries. WHO THIS BOOK IS FOR This book is for anyone who wants to build an AI app without writing any code. It is also helpful for current and aspiring AI and Machine Learning professionals who are looking to build automated, intelligent, and smart AI-based solutions. TABLE OF CONTENTS 1. What is AI? 2. Getting Started with No-Code AI 3. Building AI Model to Predict Housing Prices 4. Classifying Different Images 5. Building AI Model to Perform Sales Forecasting 6. Building AI Model to Find Fraudulent Claims 7. Building AI Model to Detect Diseases in Plants 8. Building AI Model to Create Targeted Customer Offerings 9. Building AI Model for Healthcare Information Identification 10. Building AI Model for Video Action Recognition 11. Building AI Applications with Coded AI


Data Engineering with Google Cloud Platform

Data Engineering with Google Cloud Platform

Author: Adi Wijaya

Publisher: Packt Publishing Ltd

Published: 2024-04-30

Total Pages: 476

ISBN-13: 1835085369

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Become a successful data engineer by building and deploying your own data pipelines on Google Cloud, including making key architectural decisions Key Features Get up to speed with data governance on Google Cloud Learn how to use various Google Cloud products like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream Boost your confidence by getting Google Cloud data engineering certification guidance from real exam experiences Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe second edition of Data Engineering with Google Cloud builds upon the success of the first edition by offering enhanced clarity and depth to data professionals navigating the intricate landscape of data engineering. Beyond its foundational lessons, this new edition delves into the essential realm of data governance within Google Cloud, providing you with invaluable insights into managing and optimizing data resources effectively. Written by a Data Strategic Cloud Engineer at Google, this book helps you stay ahead of the curve by guiding you through the latest technological advancements in the Google Cloud ecosystem. You’ll cover essential aspects, from exploring Cloud Composer 2 to the evolution of Airflow 2.5. Additionally, you’ll explore how to work with cutting-edge tools like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream to perform data governance on datasets. By the end of this book, you'll be equipped to navigate the ever-evolving world of data engineering on Google Cloud, from foundational principles to cutting-edge practices.What you will learn Load data into BigQuery and materialize its output Focus on data pipeline orchestration using Cloud Composer Formulate Airflow jobs to orchestrate and automate a data warehouse Establish a Hadoop data lake, generate ephemeral clusters, and execute jobs on the Dataproc cluster Harness Pub/Sub for messaging and ingestion for event-driven systems Apply Dataflow to conduct ETL on streaming data Implement data governance services on Google Cloud Who this book is for Data analysts, IT practitioners, software engineers, or any data enthusiasts looking to have a successful data engineering career will find this book invaluable. Additionally, experienced data professionals who want to start using Google Cloud to build data platforms will get clear insights on how to navigate the path. Whether you're a beginner who wants to explore the fundamentals or a seasoned professional seeking to learn the latest data engineering concepts, this book is for you.


Official Google Cloud Certified Professional Machine Learning Engineer Study Guide

Official Google Cloud Certified Professional Machine Learning Engineer Study Guide

Author: Mona Mona

Publisher: John Wiley & Sons

Published: 2023-10-27

Total Pages: 460

ISBN-13: 1119981565

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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 Digital Leader Certification Guide

Google Cloud Digital Leader Certification Guide

Author: Bruno Beraldo Rodrigues

Publisher: Packt Publishing Ltd

Published: 2024-03-15

Total Pages: 210

ISBN-13: 1805125907

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Gain the expertise needed for the Google Cloud Digital Leader certification with the help of industry insights, effective testing strategies, and exam questions designed to help you make informed tech decisions aligned with business goals Key Features Learn about data management, AI, monetization, security, and the significance of infrastructure modernization Build a solid foundation in Google Cloud, covering all technical essentials necessary for a Google Cloud Digital Leader Test your knowledge of cloud and digital transformation through realistic exam questions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionTo thrive in today's world, leaders and technologists must understand how technology shapes businesses. As organizations shift from self-hosted to cloud-native solutions, embracing serverless systems, strategizing data use, and defining monetization becomes imperative. The Google Cloud Digital Leader Certification Guide lays a solid foundation of industry knowledge, focused on the Google Cloud platform and the innovative ways in which customers leverage its technologies. The book starts by helping you grasp the essence of digital transformation within the Google Cloud context. You’ll then cover core components of the platform, such as infrastructure and application modernization, data innovation, and best practices for environment management and security. With a series of practice exam questions included, this book ensures that you build comprehensive knowledge and prepare to certify as a Google Cloud Digital Leader. Going beyond the exam essentials, you’ll also explore how companies are modernizing infrastructure, data ecosystems, and teams in order to capitalize on new market opportunities through platform expertise, best practices, and real-world scenarios. By the end of this book, you'll have learned everything you need to pass the Google Cloud Digital Leader certification exam and have a reference guide for future requirements.What you will learn Leverage Google Cloud’s AI and ML solutions to create business value Identify Google Cloud solutions for data management and smart analytics Acquire the skills necessary to modernize infrastructure and applications on GCP Understand the value of APIs and their applications in cloud environments Master financial governance and implement best practices for cost management Understand the cloud security approach and benefits of Google Cloud security Find out how IT operations must adapt to thrive in the cloud Who this book is for This Google Cloud fundamentals book is suitable for individuals with both technical and non-technical backgrounds looking for a starting point to pursue more advanced Google Cloud certifications. No prior experience is required to get started with this book; only a keen interest in learning and exploring cloud concepts, with a focus on Google Cloud.


A Guide to the Classification Theorem for Compact Surfaces

A Guide to the Classification Theorem for Compact Surfaces

Author: Jean Gallier

Publisher: Springer Science & Business Media

Published: 2013-02-05

Total Pages: 184

ISBN-13: 3642343643

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This welcome boon for students of algebraic topology cuts a much-needed central path between other texts whose treatment of the classification theorem for compact surfaces is either too formalized and complex for those without detailed background knowledge, or too informal to afford students a comprehensive insight into the subject. Its dedicated, student-centred approach details a near-complete proof of this theorem, widely admired for its efficacy and formal beauty. The authors present the technical tools needed to deploy the method effectively as well as demonstrating their use in a clearly structured, worked example. Ideal for students whose mastery of algebraic topology may be a work-in-progress, the text introduces key notions such as fundamental groups, homology groups, and the Euler-Poincaré characteristic. These prerequisites are the subject of detailed appendices that enable focused, discrete learning where it is required, without interrupting the carefully planned structure of the core exposition. Gently guiding readers through the principles, theory, and applications of the classification theorem, the authors aim to foster genuine confidence in its use and in so doing encourage readers to move on to a deeper exploration of the versatile and valuable techniques available in algebraic topology.


Google Professional Cloud Developer Exam Guide

Google Professional Cloud Developer Exam Guide

Author: Fiifi Baidoo

Publisher: BPB Publications

Published: 2023-10-27

Total Pages: 278

ISBN-13: 9355515952

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Get the knowledge and skills you need to become a certified Google Cloud Developer KEY FEATURES ● Learn everything you need to know about the Google Professional Cloud Developer exam and its objectives. ● Explore the different services GCP offers, such as Compute Engine, Cloud Storage, and Cloud SQL. ● Test your knowledge and prepare for the exam with practice exercises and quizzes. DESCRIPTION The Google Professional Cloud Developer Exam Guide is a comprehensive study guide for the Google Professional Cloud Developer exam. It covers all the topics you need to master to design, develop, deploy, and manage cloud-native applications on Google Cloud Platform (GCP). The book starts with an introduction to the certification and the skills and knowledge you need to pass the exam. Then, it covers the different development environments for GCP development, the most important GCP products and services, and the principles of designing high-performance and secure applications. The book also covers designing and building cloud-native applications, different application deployment strategies, and how to deploy apps and services on GCP. It also shows how to integrate applications with GCP services and how to monitor and manage app workloads. To help you prepare for the exam, the book ends with a chapter of quiz solutions. Overall, this book is a great resource for anyone preparing for the Google Professional Cloud Developer exam. WHAT YOU WILL LEARN ● Learn about the basics of cloud computing, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). ● Learn about serverless architectures and how to use them to build scalable and reliable applications. ● Learn how to debug and profile code to improve its performance and reliability. ● Learn about source control management and how to use it to track changes to code. ● Learn about performance testing and how to use it to ensure that applications meet their performance requirements. ● Learn about service-level agreements (SLAs), service-level objectives (SLOs), and service-level indicators (SLIs) and how to use them to measure the performance of applications. WHO THIS BOOK IS FOR This book is for software engineers, developers, and IT professionals who want to learn about cloud computing and how to develop and deploy applications on Google Cloud Platform. Readers should have a basic understanding of programming and cloud computing concepts. TABLE OF CONTENTS 1. The Professional Cloud Developer 2. Development Environments 3. GCP Products and Services 4. Designing High-performance Applications 5. Designing and Managing Secure Applications 6. Writing and Building Cloud-native Applications 7. Application Deployment Strategies 8. Deploying Apps and Services 9. Integrating Applications with GCP Services 10. Monitoring and Managing App Workloads 11. Answers to Quizzes


Professional Cloud Architect Google Cloud Certification Guide

Professional Cloud Architect Google Cloud Certification Guide

Author: Konrad Clapa

Publisher: Packt Publishing Ltd

Published: 2021-12-23

Total Pages: 664

ISBN-13: 1801811415

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Become a Professional Cloud Architect by exploring the essential concepts, tools, and services in GCP and working through practice tests designed to help you take the exam confidently Key FeaturesPlan and design a GCP cloud solution architectureEnsure the security and reliability of your cloud solutions and operationsAssess your knowledge by taking mock tests with up-to-date exam questionsBook Description Google Cloud Platform (GCP) is one of the industry leaders thanks to its array of services that can be leveraged by organizations to bring the best out of their infrastructure. This book is a comprehensive guide for learning methods to effectively utilize GCP services and help you become acquainted with the topics required to pass Google's Professional Cloud Architect certification exam. Following the Professional Cloud Architect's official exam syllabus, you'll first be introduced to the GCP. The book then covers the core services that GCP offers, such as computing and storage, and takes you through effective methods of scaling and automating your cloud infrastructure. As you progress through the chapters, you'll get to grips with containers and services and discover best practices related to the design and process. This revised second edition features new topics such as Cloud Run, Anthos, Data Fusion, Composer, and Data Catalog. By the end of this book, you'll have gained the knowledge required to take and pass the Google Cloud Certification – Professional Cloud Architect exam and become an expert in GCP services. What you will learnUnderstand the benefits of being a Google Certified Professional Cloud ArchitectFind out how to enroll for the Professional Cloud Architect examMaster the compute options in GCPExplore security and networking options in GCPGet to grips with managing and monitoring your workloads in GCPUnderstand storage, big data, and machine learning servicesBecome familiar with exam scenarios and passing strategiesWho this book is for If you are a cloud architect, cloud engineer, administrator, or any IT professional looking to learn how to implement Google Cloud services in your organization and become a GCP Certified Professional Cloud Architect, this book is for you. Basic knowledge of server infrastructure, including Linux and Windows Servers, is assumed. A solid understanding of network and storage will help you to make the most out of this book.