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Author: Jasmeet Bhatia Publisher: Packt Publishing Ltd ISBN: 1801813329 Category : Computers Languages : en Pages : 422
Book Description
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.
Author: Jasmeet Bhatia Publisher: Packt Publishing Ltd ISBN: 1801813329 Category : Computers Languages : en Pages : 422
Book Description
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.
Author: Jasmeet Bhatia Publisher: Packt Publishing Ltd ISBN: 1801813329 Category : Computers Languages : en Pages : 422
Book Description
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.
Author: Hemanth Kumar K Publisher: BPB Publications ISBN: 9355515359 Category : Computers Languages : en Pages : 308
Book Description
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
Author: Lee Boonstra Publisher: ISBN: 9781484270158 Category : Languages : en Pages : 0
Book Description
Build enterprise chatbots for web, social media, voice assistants, IoT, and telephony contact centers with Google's Dialogflow conversational AI technology. This book will explain how to get started with conversational AI using Google and how enterprise users can use Dialogflow as part of Google Cloud. It will cover the core concepts such as Dialogflow essentials, deploying chatbots on web and social media channels, and building voice agents including advanced tips and tricks such as intents, entities, and working with context. The Definitive Guide to Conversational AI with Dialogflow and Google Cloud also explains how to build multilingual chatbots, orchestrate sub chatbots into a bigger conversational platform, use virtual agent analytics with popular tools, such as BigQuery or Chatbase, and build voice bots. It concludes with coverage of more advanced use cases, such as building fulfillment functionality, building your own integrations, securing your chatbots, and building your own voice platform with the Dialogflow SDK and other Google Cloud machine learning APIs. After reading this book, you will understand how to build cross-channel enterprise bots with popular Google tools such as Dialogflow, Google Cloud AI, Cloud Run, Cloud Functions, and Chatbase. You will: Discover Dialogflow, Dialogflow Essentials, Dialogflow CX, and how machine learning is used Create Dialogflow projects for individuals and enterprise usage Work with Dialogflow essential concepts such as intents, entities, custom entities, system entities, composites, and how to track context Build bots quickly using prebuilt agents, small talk modules, and FAQ knowledge bases Use Dialogflow for an out-of-the-box agent review Deploy text conversational UIs for web and social media channels Build voice agents for voice assistants, phone gateways, and contact centers Create multilingual chatbots Orchestrate many sub-chatbots to build a bigger conversational platform Use chatbot analytics and test the quality of your Dialogflow agent See the new Dialogflow CX concepts, how Dialogflow CX fits in, and what's different in Dialogflow CX.
Author: Mona Mona Publisher: John Wiley & Sons ISBN: 1119981565 Category : Computers Languages : en Pages : 460
Book Description
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.
Author: Adi Wijaya Publisher: Packt Publishing Ltd ISBN: 1835085369 Category : Computers Languages : en Pages : 476
Book Description
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 invaluable insights into managing and optimizing data resources effectively. Furthermore, 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.
Author: Bruno Beraldo Rodrigues Publisher: Packt Publishing Ltd ISBN: 1805125907 Category : Computers Languages : en Pages : 210
Book Description
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.
Author: Mona Mona Publisher: John Wiley & Sons ISBN: 1119981565 Category : Computers Languages : en Pages : 460
Book Description
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.
Author: Jean Gallier Publisher: Springer Science & Business Media ISBN: 3642343643 Category : Mathematics Languages : en Pages : 184
Book Description
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.
Author: Fiifi Baidoo Publisher: BPB Publications ISBN: 9355515952 Category : Computers Languages : en Pages : 278
Book Description
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
Author: Jasmeet Bhatia
Author: Jasmeet Bhatia
Author: Hemanth Kumar K
Author: Lee Boonstra
Author: Mona Mona
Author: Adi Wijaya
Author: Bruno Beraldo Rodrigues
Author: Jean Gallier
Author: Fiifi Baidoo