Visualizing Google Cloud

Author: Priyanka Vergadia
Publisher: John Wiley & Sons
ISBN: 1119816335
Category : Computers
Languages : en
Pages : 497

Book Description
Easy-to-follow visual walkthrough of every important part of the Google Cloud Platform The Google Cloud Platform incorporates dozens of specialized services that enable organizations to offload technological needs onto the cloud. From routine IT operations like storage to sophisticated new capabilities including artificial intelligence and machine learning, the Google Cloud Platform offers enterprises the opportunity to scale and grow efficiently. In Visualizing Google Cloud: Illustrated References for Cloud Engineers & Architects, Google Cloud expert Priyanka Vergadia delivers a fully illustrated, visual guide to matching the best Google Cloud Platform services to your own unique use cases. After a brief introduction to the major categories of cloud services offered by Google, the author offers approximately 100 solutions divided into eight categories of services included in Google Cloud Platform: Compute Storage Databases Data Analytics Data Science, Machine Learning and Artificial Intelligence Application Development and Modernization with Containers Networking Security You’ll find richly illustrated flowcharts and decision diagrams with straightforward explanations in each category, making it easy to adopt and adapt Google’s cloud services to your use cases. With coverage of the major categories of cloud models—including infrastructure-, containers-, platforms-, functions-, and serverless—and discussions of storage types, databases and Machine Learning choices, Visualizing Google Cloud: Illustrated References for Cloud Engineers & Architects is perfect for every Google Cloud enthusiast, of course. It is for anyone who is planning a cloud migration or new cloud deployment. It is for anyone preparing for cloud certification, and for anyone looking to make the most of Google Cloud. It is for cloud solutions architects, IT decision-makers, and cloud data and ML engineers. In short, this book is for YOU.

Visualizing Google Cloud

Author: Priyanka Vergadia
Publisher: John Wiley & Sons
ISBN: 1119816335
Category : Computers
Languages : en
Pages : 497

Google Cloud for Developers

Author: Hector Parra Martinez
Publisher: Packt Publishing Ltd
ISBN: 1837636273
Category : Computers
Languages : en
Pages : 364

Book Description
Unlock your potential with this ultimate guide to Google Cloud – packed with expert tips, coding techniques, legacy migration, and application extension strategies Purchase of the print or Kindle book includes a free PDF eBook Key Features Maximize your code potential using Google Cloud services Migrate legacy code to the cloud seamlessly and create code that runs anywhere Use hands-on examples to learn and showcase your experience with Google Cloud Book Description As more organizations embrace cloud computing, developers new to the cloud often feel overwhelmed by cloud migration and code running directly on the cloud. Google Cloud for Developers comes packed with practical tips and expert advice to accelerate your application development journey and help you unlock the full potential of cloud computing. You'll begin by understanding and comparing all the available options to run your code. You'll write, deploy, monitor, and troubleshoot your code without leaving the Google Cloud IDE while selecting the best option – serverless or GKE containers – for each use case. After that, you'll get to grips with the basic Google Cloud infrastructure services and connect your code with public APIs. This will help you add features to your application, such as language translation and object detection in images or videos. Furthermore, you'll explore a comprehensive list of tips and best practices to make your migration smooth. You'll also gain the necessary knowledge to write code from scratch, by employing the basics of hybrid cloud applications and build services that can run virtually anywhere. By the end of this book, you'll be well equipped to carry out the application development process and successfully move your code to Google Cloud. What you will learn Understand how to write, run, and troubleshoot code on Google Cloud Choose between serverless or GKE containers for running your code Connect your code to Google Cloud services using public APIs Migrate your code to Google Cloud flawlessly Build hybrid cloud solutions that can run virtually anywhere Get to grips with Cloud Functions, App Engine, GKE, and Anthos Who this book is for Google Cloud for Developers is for cloud architects, engineers, or developers willing to migrate their applications and services to Google Cloud or build them from scratch. Entrepreneurs in early-stage start-ups and IT professionals who want to know more about Google Cloud from a developer perspective will also benefit from this book. A basic understanding of Cloud concepts and basic experience in writing Python and Shell scripts is a must.

Data Engineering with Google Cloud Platform

Author: Adi Wijaya
Publisher: Packt Publishing Ltd
ISBN: 1800565062
Category : Computers
Languages : en
Pages : 440

Book Description
Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data engineer Key Features Understand data engineering concepts, the role of a data engineer, and the benefits of using GCP for building your solution Learn how to use the various GCP products to ingest, consume, and transform data and orchestrate pipelines Discover tips to prepare for and pass the Professional Data Engineer exam Book DescriptionWith this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards. Starting with a quick overview of the fundamental concepts of data engineering, you'll learn the various responsibilities of a data engineer and how GCP plays a vital role in fulfilling those responsibilities. As you progress through the chapters, you'll be able to leverage GCP products to build a sample data warehouse using Cloud Storage and BigQuery and a data lake using Dataproc. The book gradually takes you through operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. You'll learn how to design IAM for data governance, deploy ML pipelines with the Vertex AI, leverage pre-built GCP models as a service, and visualize data with Google Data Studio to build compelling reports. Finally, you'll find tips on how to boost your career as a data engineer, take the Professional Data Engineer certification exam, and get ready to become an expert in data engineering with GCP. By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP.What you will learn Load data into BigQuery and materialize its output for downstream consumption Build data pipeline orchestration using Cloud Composer Develop Airflow jobs to orchestrate and automate a data warehouse Build a Hadoop data lake, create ephemeral clusters, and run jobs on the Dataproc cluster Leverage Pub/Sub for messaging and ingestion for event-driven systems Use Dataflow to perform ETL on streaming data Unlock the power of your data with Data Studio Calculate the GCP cost estimation for your end-to-end data solutions Who this book is for This book is for data engineers, data analysts, and anyone looking to design and manage data processing pipelines using GCP. You'll find this book useful if you are preparing to take Google's Professional Data Engineer exam. Beginner-level understanding of data science, the Python programming language, and Linux commands is necessary. A basic understanding of data processing and cloud computing, in general, will help you make the most out of this book.

Cloud Analytics with Google Cloud Platform

Author: Sanket Thodge
Publisher: Packt Publishing Ltd
ISBN: 1788838599
Category : Computers
Languages : en
Pages : 273

Book Description
Combine the power of analytics and cloud computing for faster and efficient insights Key Features Master the concept of analytics on the cloud: and how organizations are using it Learn the design considerations and while applying a cloud analytics solution Design an end-to-end analytics pipeline on the cloud Book Description With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machine learning and deep learning. By the end of this book, you will have a better understanding of cloud analytics as a concept as well as a practical know-how of its implementation What you will learn Explore the basics of cloud analytics and the major cloud solutions Learn how organizations are using cloud analytics to improve the ROI Explore the design considerations while adopting cloud services Work with the ingestion and storage tools of GCP such as Cloud Pub/Sub Process your data with tools such as Cloud Dataproc, BigQuery, etc Over 70 GCP tools to build an analytics engine for cloud analytics Implement machine learning and other AI techniques on GCP Who this book is for This book is targeted at CIOs, CTOs, and even analytics professionals looking for various alternatives to implement their analytics pipeline on the cloud. Data professionals looking to get started with cloud-based analytics will also find this book useful. Some basic exposure to cloud platforms such as GCP will be helpful, but not mandatory.

Official Google Cloud Certified Professional Machine Learning Engineer Study Guide

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.

Official Google Cloud Certified Professional Data Engineer Study Guide

Author: Dan Sullivan
Publisher: John Wiley & Sons
ISBN: 1119618452
Category : Computers
Languages : en
Pages : 357

Book Description
The proven Study Guide that prepares you for this new Google Cloud exam The Google Cloud Certified Professional Data Engineer Study Guide, provides everything you need to prepare for this important exam and master the skills necessary to land that coveted Google Cloud Professional Data Engineer certification. Beginning with a pre-book assessment quiz to evaluate what you know before you begin, each chapter features exam objectives and review questions, plus the online learning environment includes additional complete practice tests. Written by Dan Sullivan, a popular and experienced online course author for machine learning, big data, and Cloud topics, Google Cloud Certified Professional Data Engineer Study Guide is your ace in the hole for deploying and managing analytics and machine learning applications. Build and operationalize storage systems, pipelines, and compute infrastructure Understand machine learning models and learn how to select pre-built models Monitor and troubleshoot machine learning models Design analytics and machine learning applications that are secure, scalable, and highly available. This exam guide is designed to help you develop an in depth understanding of data engineering and machine learning on Google Cloud Platform.

Building Machine Learning and Deep Learning Models on Google Cloud Platform

Author: Ekaba Bisong
Publisher: Apress
ISBN: 1484244702
Category : Computers
Languages : en
Pages : 703

Book Description
Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. What You’ll Learn Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your resultsKnow the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products Who This Book Is For Beginners to the practice of data science and applied machine learning, data scientists at all levels, machine learning engineers, Google Cloud Platform data engineers/architects, and software developers

Creating AI Synergy Through Business Technology Transformation

Author: Sundaramurthy, Balaji
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 414

Book Description
Companies constantly strive to adopt the latest technological advancements in order to stay ahead in today's interconnected world. However, many organizations need guidance to fully leverage the potential of artificial intelligence (AI) and digital transformation. Without this direction, their ability to drive growth and efficiency is thwarted. Creating AI Synergy Through Business Technology Transformation offers a comprehensive guide to leveraging AI and digital transformation for strategic advantage. By combining insightful research, practical case studies, and innovative strategies, this book provides a roadmap for organizations to maximize the benefits of AI across their operations. From optimizing decision-making processes to enhancing customer experiences, the book demonstrates how AI can revolutionize business practices and drive sustainable growth.

Data Exploration and Preparation with BigQuery

Author: Mike Kahn
Publisher: Packt Publishing Ltd
ISBN: 1805123424
Category : Computers
Languages : en
Pages : 264

Book Description
Leverage BigQuery to understand and prepare your data to ensure that it's accurate, reliable, and ready for analysis and modeling Key Features Use mock datasets to explore data with the BigQuery web UI, bq CLI, and BigQuery API in the Cloud console Master optimization techniques for storage and query performance in BigQuery Engage with case studies on data exploration and preparation for advertising, transportation, and customer support data Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData professionals encounter a multitude of challenges such as handling large volumes of data, dealing with data silos, and the lack of appropriate tools. Datasets often arrive in different conditions and formats, demanding considerable time from analysts, engineers, and scientists to process and uncover insights. The complexity of the data life cycle often hinders teams and organizations from extracting the desired value from their data assets. Data Exploration and Preparation with BigQuery offers a holistic solution to these challenges. The book begins with the basics of BigQuery while covering the fundamentals of data exploration and preparation. It then progresses to demonstrate how to use BigQuery for these tasks and explores the array of big data tools at your disposal within the Google Cloud ecosystem. The book doesn’t merely offer theoretical insights; it’s a hands-on companion that walks you through properly structuring your tables for query efficiency and ensures adherence to data preparation best practices. You’ll also learn when to use Dataflow, BigQuery, and Dataprep for ETL and ELT workflows. The book will skillfully guide you through various case studies, demonstrating how BigQuery can be used to solve real-world data problems. By the end of this book, you’ll have mastered the use of SQL to explore and prepare datasets in BigQuery, unlocking deeper insights from data.What you will learn Assess the quality of a dataset and learn best practices for data cleansing Prepare data for analysis, visualization, and machine learning Explore approaches to data visualization in BigQuery Apply acquired knowledge to real-life scenarios and design patterns Set up and organize BigQuery resources Use SQL and other tools to navigate datasets Implement best practices to query BigQuery datasets Gain proficiency in using data preparation tools, techniques, and strategies Who this book is for This book is for data analysts seeking to enhance their data exploration and preparation skills using BigQuery. It guides anyone using BigQuery as a data warehouse to extract business insights from large datasets. A basic understanding of SQL, reporting, data modeling, and transformations will assist with understanding the topics covered in this book.