Exam Ref 70-774 Perform Cloud Data Science with Azure Machine Learning PDF Download

Author: Ginger Grant
Publisher: Microsoft Press
ISBN: 013484968X
Category : Computers
Languages : en
Pages : 566

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Book Description
Prepare for Microsoft Exam 70-774–and help demonstrate your real-world mastery of performing key data science activities with Azure Machine Learning services. Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the MCSA level. Focus on the expertise measured by these objectives: Prepare data for analysis in Azure Machine Learning and export from Azure Machine Learning Develop machine learning models Operationalize and manage Azure Machine Learning Services Use other services for machine learning This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you are familiar with Azure data services, machine learning concepts, and common data science processes About the Exam Exam 70-774 focuses on skills and knowledge needed to prepare data for analysis with Azure Machine Learning; find key variables describing your data’s behavior; develop models and identify optimal algorithms; train, validate, deploy, manage, and consume Azure Machine Learning Models; and leverage related services and APIs. About Microsoft Certification Passing this exam as well as Exam 70-773: Analyzing Big Data with Microsoft R earns your MCSA: Machine Learning certifi¿cation, demonstrating your expertise in operationalizing Microsoft Azure machine learning and Big Data with R Server and SQL R Services. See full details at: microsoft.com/learning

Author: Andreas Botsikas
Publisher: Packt Publishing Ltd
ISBN: 1800561261
Category : Computers
Languages : en
Pages : 448

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Book Description
Develop the skills you need to run machine learning workloads in Azure and pass the DP-100 exam with ease Key FeaturesCreate end-to-end machine learning training pipelines, with or without codeTrack experiment progress using the cloud-based MLflow-compatible process of Azure ML servicesOperationalize your machine learning models by creating batch and real-time endpointsBook Description The Azure Data Scientist Associate Certification Guide helps you acquire practical knowledge for machine learning experimentation on Azure. It covers everything you need to pass the DP-100 exam and become a certified Azure Data Scientist Associate. Starting with an introduction to data science, you'll learn the terminology that will be used throughout the book and then move on to the Azure Machine Learning (Azure ML) workspace. You'll discover the studio interface and manage various components, such as data stores and compute clusters. Next, the book focuses on no-code and low-code experimentation, and shows you how to use the Automated ML wizard to locate and deploy optimal models for your dataset. You'll also learn how to run end-to-end data science experiments using the designer provided in Azure ML Studio. You'll then explore the Azure ML Software Development Kit (SDK) for Python and advance to creating experiments and publishing models using code. The book also guides you in optimizing your model's hyperparameters using Hyperdrive before demonstrating how to use responsible AI tools to interpret and debug your models. Once you have a trained model, you'll learn to operationalize it for batch or real-time inferences and monitor it in production. By the end of this Azure certification study guide, you'll have gained the knowledge and the practical skills required to pass the DP-100 exam. What you will learnCreate a working environment for data science workloads on AzureRun data experiments using Azure Machine Learning servicesCreate training and inference pipelines using the designer or codeDiscover the best model for your dataset using Automated MLUse hyperparameter tuning to optimize trained modelsDeploy, use, and monitor models in productionInterpret the predictions of a trained modelWho this book is for This book is for developers who want to infuse their applications with AI capabilities and data scientists looking to scale their machine learning experiments in the Azure cloud. Basic knowledge of Python is needed to follow the code samples used in the book. Some experience in training machine learning models in Python using common frameworks like scikit-learn will help you understand the content more easily.

Author: Julian Sharp
Publisher: Microsoft Press
ISBN: 0137358148
Category : Computers
Languages : en
Pages : 288

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Book Description
Prepare for Microsoft Exam AI-900 and help demonstrate your real-world knowledge of diverse machine learning (ML) and artificial intelligence (AI) workloads, and how they can be implemented with Azure AI. Designed for business stakeholders, new and existing IT professionals, consultants, and students, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure AI Fundamentals level. Focus on the expertise measured by these objectives: • Describe AI workloads and considerations • Describe fundamental principles of machine learning on Azure • Describe features of computer vision workloads on Azure • Describe features of Natural Language Processing (NLP) workloads on Azure • Describe features of conversational AI workloads on Azure This Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you are a business user, stakeholder, technical professional, or student who wants to become familiar with Azure AI; requires no data science or software engineering experience. About the Exam Exam AI-900 focuses on knowledge needed to identify features of common AI workloads and guiding principles for responsible AI; identify common ML types; describe core ML concepts; identify core tasks in creating an ML solution; describe capabilities of no-code ML with Azure Machine Learning Studio; identify common types of computer vision solutions; identify Azure tools and services for computer vision tasks; identify features of common NLP workload scenarios; identify Azure tools and services for NLP workloads; and identify common use cases and Azure services for conversational Al. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Azure AI Fundamentals certification, demonstrating your knowledge of common ML and AI workloads and how to implement them on Azure. With this certification, you can move on to earn more advanced role-based certifications, including Microsoft Certified: Azure AI Engineer Associate or Azure Data Scientist Associate. See full details at: microsoft.com/learn

Author: Zoiner Tejada
Publisher: Pearson Education
ISBN: 0735697043
Category : Computers
Languages : en
Pages : 433

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Book Description
Prepare for Microsoft Exam 70-532--and help demonstrate your real-world mastery of Microsoft Azure solution development. Designed for experienced developers ready to advance their status, Exam Ref focuses on the critical-thinking and decision-making acumen needed for success at the Microsoft Specialist level. Focus on the expertise measured by these objectives: Design and implement Websites Create and manage Virtual Machines Design and implement Cloud Services Design and implement a storage strategy Manage application and network services This Microsoft Exam Ref : Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Will be valuable for Microsoft Azure developers, solution architects, DevOps engineers, and QA engineers Assumes you have experience designing, programming, implementing, automating, and monitoring Microsoft Azure solutions and that you are proficient with tools, techniques, and approaches for building scalable, resilient solutions Developing Microsoft Azure Solutions About the Exam Exam 70-532 focuses on the skills and knowledge needed to develop Microsoft Azure solutions that include websites, virtual machines, cloud services, storage, application services, and network services. About Microsoft Certification Passing this exam earns you a Microsoft Specialist certification in Microsoft Azure, demonstrating your expertise with the Microsoft Azure enterprise-grade cloud platform. You can earn this certification by passing Exam 70-532, Developing Microsoft Azure Solutions; or Exam 70-533, Implementing Microsoft Azure Infrastructure Solutions; or Exam 70-534, Architecting Microsoft Azure Solutions. See full details at: microsoft.com/learning.

Author: Valentine Fontama
Publisher: Apress
ISBN: 148420445X
Category : Computers
Languages : en
Pages : 178

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Book Description
Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis. The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter. The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft.

Author: Zoiner Tejada
Publisher:
ISBN: 9781509304608
Category : Cloud computing
Languages : en
Pages :

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Book Description

Author: Ger Arevalo
Publisher: Ger Arevalo
ISBN:
Category : Computers
Languages : en
Pages : 16

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Book Description
This book is designed to be an ancillary to the classes, labs, and hands on practice that you have diligently worked on in preparing to obtain your DP-100: Azure Data Scientist Associate certification. I won’t bother talking about the benefits of certifications. This book tries to reinforce the knowledge that you have gained in your process of studying. It is meant as one of the end steps in your preparation for the DP-100 exam. This book is short, but It will give you a good gauge of your readiness. Learning can be seen in 4 stages: 1. Unconscious Incompetence 2. Conscious Incompetence 3. Conscious Competence 4. Unconscious Competence This book will assume the reader has already gone through the needed classes, labs, and practice. It is meant to take the reader from stage 2, Conscious Incompetence, to stage 3 Conscious Competence. At stage 3, you should be ready to take the exam. Only real-world scenarios and work experience will take you to stage 4, Unconscious Competence. Before we get started, we all have doubts when preparing to take an exam. What is your reason and purpose for taking this exam? Remember your reason and purpose when you have some doubts. Obstacle is the way. Control your mind, attitude, and you can control the situation. Persistence leads to confidence. Confidence erases doubts.

Author: Michael Washam
Publisher: Microsoft Press
ISBN: 1509304665
Category : Computers
Languages : en
Pages : 851

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Book Description
Prepare for the newest versions of Microsoft Exam 70-533–and help demonstrate your real-world mastery of implementing Microsoft Azure Infrastructure as a Service (IaaS). Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the MCSA level. Focus on the expertise measured by these objectives: Design and implement Azure App Service Apps Create and manage compute resources, and implement containers Design and implement a storage strategy, including storage encryption Implement virtual networks, including new techniques for hybrid connections Design and deploy ARM Templates Manage Azure security and Recovery Services Manage Azure operations, including automation and data analysis Manage identities with Azure AD Connect Health, Azure AD Domain Services, and Azure AD single sign on This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you are an IT professional with experience implementing and monitoring cloud and hybrid solutions and/or supporting application lifecycle management This book covers the 533 objectives as of December 2017. If there are updates for this book, you will find them at https://aka.ms/examref5332E/errata. About the Exam Exam 70-533 focuses on skills and knowledge for provisioning and managing services in Microsoft Azure, including: implementing infrastructure components such as virtual networks, virtual machines, containers, web and mobile apps, and storage; planning and managing Azure AD, and configuring Azure AD integration with on-premises Active Directory domains. About Microsoft Certification Passing this exam helps qualify you for MCSA: Cloud Platform Microsoft Certified Solutions Associate certification, demonstrating your expertise in applying Microsoft cloud technologies to reduce costs and deliver value. To earn this certification, you must also pass any one of the following exams: 70-532 Developing Microsoft Azure Solutions, or 70-534 Architecting Microsoft Azure Solutions, or 70-535, Architecting Microsoft Azure Solutions, or 70-537: Configuring and Operating a Hybrid Cloud with Microsoft Azure Stack.

Author: Aaron Guilmette
Publisher: Packt Publishing Ltd
ISBN: 1835885675
Category : Computers
Languages : en
Pages : 288

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Book Description
Get ready to pass the certification exam on your first attempt by gaining actionable insights into AI concepts, ML techniques, and Azure AI services covered in the latest AI-900 exam syllabus from two industry experts Key Features Discover Azure AI services, including computer vision, Auto ML, NLP, and OpenAI Explore AI use cases, such as image identification, chatbots, and more Work through 145 practice questions under chapter-end self-assessments and mock exams Purchase of this book unlocks access to web-based exam prep resources, including mock exams, flashcards, and exam tips Book Description The AI-900 exam helps you take your first step into an AI-shaped future. Regardless of your technical background, this book will help you test your understanding of the key AI-related topics and tools used to develop AI solutions in Azure cloud. This exam guide focuses on AI workloads, including natural language processing (NLP) and large language models (LLMs). You'll explore Microsoft's responsible AI principles like safety and accountability. Then, you'll cover the basics of machine learning (ML), including classification and deep learning, and learn how to use training and validation datasets with Azure ML. Using Azure AI Vision, face detection, and Video Indexer services, you'll get up to speed with computer vision-related topics like image classification, object detection, and facial detection. Later chapters cover NLP features such as key phrase extraction, sentiment analysis, and speech processing using Azure AI Language, speech, and translator services. The book also guides you through identifying GenAI models and leveraging Azure OpenAI Service for content generation. At the end of each chapter, you'll find chapter review questions with answers, provided as an online resource. By the end of this exam guide, you'll be able to work with AI solutions in Azure and pass the AI-900 exam using the online exam prep resources. What you will learn Discover various types of artificial intelligence (AI)workloads and services in Azure Cover Microsoft's guiding principles for responsible AI development and use Understand the fundamental principles of how AI and machine learning work Explore how AI models can recognize content in images and documents Gain insights into the features and use cases for natural language processing Explore the capabilities of generative AI services Who this book is for Whether you're a cloud engineer, software developer, an aspiring data scientist, or simply interested in learning AI/ML concepts and capabilities on Azure, this book is for you. The book also serves as a foundation for those looking to attempt more advanced AI and data science-related certification exams (e.g. Microsoft Certified: Azure AI Engineer Associate). Although no experience in data science and software engineering is required, basic knowledge of cloud concepts and client-server applications is assumed.

Author: Julian Soh
Publisher: Apress
ISBN: 9781484264041
Category : Computers
Languages : en
Pages : 285

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Book Description
Understand and learn the skills needed to use modern tools in Microsoft Azure. This book discusses how to practically apply these tools in the industry, and help drive the transformation of organizations into a knowledge and data-driven entity. It provides an end-to-end understanding of data science life cycle and the techniques to efficiently productionize workloads. The book starts with an introduction to data science and discusses the statistical techniques data scientists should know. You'll then move on to machine learning in Azure where you will review the basics of data preparation and engineering, along with Azure ML service and automated machine learning. You'll also explore Azure Databricks and learn how to deploy, create and manage the same. In the final chapters you'll go through machine learning operations in Azure followed by the practical implementation of artificial intelligence through machine learning. Data Science Solutions on Azure will reveal how the different Azure services work together using real life scenarios and how-to-build solutions in a single comprehensive cloud ecosystem. What You'll Learn Understand big data analytics with Spark in Azure Databricks Integrate with Azure services like Azure Machine Learning and Azure Synaps Deploy, publish and monitor your data science workloads with MLOps Review data abstraction, model management and versioning with GitHub Who This Book Is For Data Scientists looking to deploy end-to-end solutions on Azure with latest tools and techniques.