Dario Cabianca – författare

Prepare for the AWS Machine Learning Engineer exam smarter and faster and get job-ready with this efficient and authoritative resourceIn AWS Certified Machine Learning Engineer Study Guide: Associate (MLA-C01) Exam, veteran AWS Practice Director at Trace3—a leading IT consultancy offering AI, data, cloud and cybersecurity solutions for clients across industries—Dario Cabianca delivers a practical and up-to-date roadmap to preparing for the MLA-C01 exam. You'll learn the skills you need to succeed on the exam as well as those you need to hit the ground running at your first AI-related tech job.You'll learn how to prepare data for machine learning models on Amazon Web Services, build, train, refine models, evaluate model performance, deploy and secure your machine learning applications against bad actors.Inside the book: Complimentary access to the Sybex online test bank, which includes an assessment test, chapter review questions, practice exam, flashcards, and a searchable key term glossaryStrategies for selecting and justifying an appropriate machine learning approach for specific business problems and identifying the most efficient AWS solutions for those problemsPractical techniques you can implement immediately in an artificial intelligence and machine learning (AI/ML) development or data science rolePerfect for everyone preparing for the AWS Certified Machine Learning Engineer -- Associate exam, AWS Certified Machine Learning Engineer Study Guide is also an invaluable resource for those preparing for their first role in AI or data science, as well as junior-level practicing professionals seeking to review the fundamentals with a convenient desk reference.

Prepare for the AWS Machine Learning Engineer exam smarter and faster and get job-ready with this efficient and authoritative resource

In AWS Certified Machine Learning Engineer Study Guide: Associate (MLA-C01) Exam, veteran AWS Practice Director at Trace3—a leading IT consultancy offering AI, data, cloud and cybersecurity solutions for clients across industries—Dario Cabianca delivers a practical and up-to-date roadmap to preparing for the MLA-C01 exam. You''ll learn the skills you need to succeed on the exam as well as those you need to hit the ground running at your first AI-related tech job.

You''ll learn how to prepare data for machine learning models on Amazon Web Services, build, train, refine models, evaluate model performance, deploy and secure your machine learning applications against bad actors.

Inside the book:

Complimentary access to the Sybex online test bank, which includes an assessment test, chapter review questions, practice exam, flashcards, and a searchable key term glossary Strategies for selecting and justifying an appropriate machine learning approach for specific business problems and identifying the most efficient AWS solutions for those problems Practical techniques you can implement immediately in an artificial intelligence and machine learning (AI/ML) development or data science role

Perfect for everyone preparing for the AWS Certified Machine Learning Engineer -- Associate exam, AWS Certified Machine Learning Engineer Study Guide is also an invaluable resource for those preparing for their first role in AI or data science, as well as junior-level practicing professionals seeking to review the fundamentals with a convenient desk reference.

Prepare for the AWS Machine Learning Engineer exam smarter and faster and get job-ready with this efficient and authoritative resource

In AWS Certified Machine Learning Engineer Study Guide: Associate (MLA-C01) Exam, veteran AWS Practice Director at Trace3—a leading IT consultancy offering AI, data, cloud and cybersecurity solutions for clients across industries—Dario Cabianca delivers a practical and up-to-date roadmap to preparing for the MLA-C01 exam. You''ll learn the skills you need to succeed on the exam as well as those you need to hit the ground running at your first AI-related tech job.

You''ll learn how to prepare data for machine learning models on Amazon Web Services, build, train, refine models, evaluate model performance, deploy and secure your machine learning applications against bad actors.

Inside the book:

Complimentary access to the Sybex online test bank, which includes an assessment test, chapter review questions, practice exam, flashcards, and a searchable key term glossary Strategies for selecting and justifying an appropriate machine learning approach for specific business problems and identifying the most efficient AWS solutions for those problems Practical techniques you can implement immediately in an artificial intelligence and machine learning (AI/ML) development or data science role

Perfect for everyone preparing for the AWS Certified Machine Learning Engineer -- Associate exam, AWS Certified Machine Learning Engineer Study Guide is also an invaluable resource for those preparing for their first role in AI or data science, as well as junior-level practicing professionals seeking to review the fundamentals with a convenient desk reference.

While many guides exist to help software engineers learn cloud networking design and architecture concepts, and even prepare for cloud network certifications on AWS and Azure, far fewer resources are available covering the Google Cloud Platform (GCP) Professional Cloud Network Engineer certification exam. Well, look no further! This self-paced guide book is designed to help engineers learn cloud networking best practices on GCP, and prepare for the GCP Professional Cloud Network Engineer certification exam.You will waste no time when you use this study companion. It lets you dive in and learn how GCP differs from other public cloud providers (AWS and Microsoft Azure). You will understand GCP's unique ability to allow virtual private clouds (VPCs) that span across multiple regions. You will know how to leverage GCP as a competitive advantage in the IT engineering community. Key concepts covered on the exam are called out and applied in each chapter of this book, giving you both practice and reinforcement, a far more effective learning tool than rote learning or similar approaches typically enlisted in exam preparation.Enterprises are looking for developers with Google networking skills. Now is the time to skill up! This book shows you how to leverage GCP’s developer-focused, user-friendly approach to understand how the networking components enabling the popular 1B-user Google products (e.g., Gmail, Google Search, YouTube, Google Workspace (formerly G-Suite), Google Maps, Google Photos, and many others) work behind the scenes.What You Will LearnIn addition to preparing for the GCP Professional Cloud Network Engineer certification exam, you will learn how to:Architect and design a virtual private cloudImplement a virtual private cloudConfigure network servicesImplement hybrid connectivityImplement network securityManage network operationsOptimize network resourcesWho This Book Is ForSoftware engineers (network, DevOps, SecOps, DataOps, engineers skilled with SDLC), software architects (solution, security, data, infrastructure, cloud, those skilled with TOGAF), and IT professionals. Prerequisites: While this study companion is intended to be self-contained, a basic knowledge of cloud computing along with hands-on experience with a minimum of two modern programming languages (Java, C#) is beneficial in order for readers to fully achieve the objectives of the book.

While many guides exist to help software engineers learn cloud networking design and architecture concepts, and even prepare for cloud network certifications on AWS and Azure, far fewer resources are available covering the Google Cloud Platform (GCP) Professional Cloud Network Engineer certification exam. Well, look no further! This self-paced guide book is designed to help engineers learn cloud networking best practices on GCP, and prepare for the GCP Professional Cloud Network Engineer certification exam.

You will waste no time when you use this study companion. It lets you dive in and learn how GCP differs from other public cloud providers (AWS and Microsoft Azure). You will understand GCP''s unique ability to allow virtual private clouds (VPCs) that span across multiple regions. You will know how to leverage GCP as a competitive advantage in the IT engineering community. Key concepts covered on the exam are called out and applied in each chapter of this book, giving you both practice and reinforcement, a far more effective learning tool than rote learning or similar approaches typically enlisted in exam preparation.

Enterprises are looking for developers with Google networking skills. Now is the time to skill up! This book shows you how to leverage GCP’s developer-focused, user-friendly approach to understand how the networking components enabling the popular 1B-user Google products (e.g., Gmail, Google Search, YouTube, Google Workspace (formerly G-Suite), Google Maps, Google Photos, and many others) work behind the scenes.

What You Will Learn

In addition to preparing for the GCP Professional Cloud Network Engineer certification exam, you will learn how to:

Architect and design a virtual private cloudImplement a virtual private cloudConfigure network servicesImplement hybrid connectivityImplement network securityManage network operationsOptimize network resources

Who This Book Is For

Software engineers (network, DevOps, SecOps, DataOps, engineers skilled with SDLC), software architects (solution, security, data, infrastructure, cloud, those skilled with TOGAF), and IT professionals. Prerequisites: While this study companion is intended to be self-contained, a basic knowledge of cloud computing along with hands-on experience with a minimum of two modern programming languages (Java, C#) is beneficial in order for readers to fully achieve the objectives of the book.

Written in a simple and developer-focused style, this book gives you the tools and knowledge you need to ace the GCP Professional Cloud Security Engineer certification exam. The approach is two-fold: introducing and implementing all GCP cloud security concepts and controls based on the certification exam objectives, and demonstrating how these concepts can be applied to real-world scenarios.Your study begins with cloud identities in GCP and different identity types (user accounts, service accounts, groups, and domains) and how separation of duties is implemented with access controls and Identity and Access Management (IAM). Emphasis is placed on the unique GCP approach to managing resources, with its clear distinction between resource ownership and resource billing. Following the defense in depth principle, the book shifts focus to network security and introduces different types of constructs that enable micro-segmentation, as they are implemented in a software-defined network. A chapter devoted to data protection is included. You will learn how to leverage the Data Loss Prevention (DLP) application programming interface (API) to prevent access to your workloads’ sensitive data from unauthorized use. Examples on how to use the DLP API are provided using the Go language, which is becoming widely adopted in the developer community due to its simplicity, and high-performance networking and multi-processing capabilities. Encryption at rest, in use, and in transit is covered with an overview on how GCP implements confidential computing. The book concludes with an examination of the GCP services you need to know to monitor, audit, and ensure compliance with the laws and regulations where your workloads and infrastructure operate.By the end of the book, you will have acquired the knowledge and confidence to pass the GCP Professional Cloud Security Engineer certification exam and to successfully design, architect, and engineer security solutions with the Google Cloud Platform.Bonus Material: IAM deny policiesWhat You Will Learn Understand the five security principles and how to use them to drive the development of modern security architectures in Google CloudSecure identities with Cloud Identity and Identity & Access Management (IAM)Secure the network with segmentation and private connectivityProtect sensitive data with the Data Loss Prevention (DLP) API and encryptionMonitor, log, audit, and troubleshoot security incidents with the Google Cloud Operations SuiteEnsure compliance and address regulatory concerns    Who This Book Is ForSoftware engineers specializing in DevOps, SecOps, and DataOps, who possess expertise in the Software Development Life Cycle (SDLC) methodologies within Agile teams. It also targets software architects with proficiency in various domains such as security, network, solution, data, infrastructure, cloud, and enterprise architecture.