Azure Data Scientist Associate Certification Guide: DP-100 exam (2021)

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BIRMINGHAM—MUMBAIAzure Data Scientist AssociateCertification GuideCopyright © 2021 Packt PublishingAll rights reserved. No part of this book may be reproduced, stored in aretrieval system, or transmitted in any form or by any means, without theprior written permission of the publisher, except in the case of briefquotations embedded in critical articles or reviews.Every effort has been made in the preparation of this book to ensure theaccuracy of the information presented. However, the information contained inthis book is sold without warranty, either express or implied. Neither theauthors, nor Packt Publishing or its dealers and distributors, will be heldliable for any damages caused or alleged to have been caused directly orindirectly by this book.Packt Publishing has endeavored to provide trademark information about allof the companies and products mentioned in this book by the appropriate useof capitals. However, Packt Publishing cannot guarantee the accuracy of thisinformation.Publishing Product Manager: Aditi Gour

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Senior Editor: David SugarmanContent Development Editor: Nathanya DiasTechnical Editor: Sonam PandeyCopy Editor: Safis EditingProject Coordinator: Aparna Ravikumar NairProofreader: Safis EditingIndexer: Tejal Daruwale SoniProduction Designer: Vijay KambleFirst published: December 2021Production reference: 1291021Published by Packt Publishing Ltd.Livery Place35 Livery StreetBirminghamB3 2PB, UK.ISBN 978-1-80056-500-5www.packt.comContributorsAbout the authors

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Andreas Botsikasis an experienced advisor working in the softwareindustry. He has worked in the finance sector, leading highly efficientDevOps teams, and architecting and building high-volume transactionalsystems. He then traveled the world, building AI-infused solutions with agroup of engineers and data scientists. Currently, he works as a trustedadvisor for customers onboarding into Azure, de-risking and acceleratingtheir cloud journey. He is a strong engineering professional with a Doctor ofPhilosophy (Ph.D.) in resource optimization with artificial intelligence fromthe National Technical University of Athens.

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I want to thank the people who have been close to me and supported me,especially my family. Moreover, I would like to thank the Packt teamand the reviewers for the tremendous support throughout the bookauthoring process. Finally, I would like to thank Michael, whochallenged me to co-write this book. The journey was long, full ofadventures, full of discoveries, exactly as I was hoping it to be.

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2c9d7257ca15856e46c7c35e30d138cfMichael Hlobilis an experienced architect focused on quickly understandingcustomers' business needs, with over 25 years of experience in IT pitfalls andsuccessful projects, and is dedicated to creating solutions based on theMicrosoft Platform. He has an MBA in Computer Science and Economics(from the Technical University and the University of Vienna) and an MSc(from the ESBA) in Systemic Coaching. He was working on advancedanalytics projects in the last decade, including massive parallel systems andMachine Learning systems. He enjoys working with customers andsupporting the journey to the cloud.

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I would like to first and foremost thank my grandparents: “Oma andOpa Danke für eure unermüdliche Unterstützung ohne euch wäre ichnicht das geworden was ich bin!“. Moreover, I would like to thank myfamily. My wife and my three kids: “Danke für alles was ich lernendurfte und lernen darf!“. A huge thank you to Andreas: "Ευχαριστώ γιατην υπομονή και τη φιλία σου!". Last but not least to the Packt team andthe reviewers for the tremendous work they did throughout the bookauthoring process.I have known Andreas and Michael from our FastTrack for Azureorganization. Our core strategy is to meet customers wherever they are intheir current cloud journey – primarily to accelerate and de-risk clouddeployments at scale while improving the Azure platform. Both are enablingcustomers all over the world to become successful with their ArtificialIntelligence projects. AI plays a crucial role in the digital revolution weexperience every day. There are challenges with every new technology,especially when it comes to building trust in the latest technology. This bookcovers both how to produce AI but also covers aspects of buildingresponsible AI. I think these two aspects makes this book so valuable. I hopeyou enjoy it.Juergen Daiberl, General Manager - FastTrack for Azure LeadThe exponential growth of data and the rapid evolution of cloud computinghave put topics such as data science and machine learning on top of theagenda for many organizations. Andreas and Michael’s long experience withhundreds of our customers comes together in this book, combining theconcepts of AI with practical guidance on how to use it in real life scenarios,

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using the Microsoft Azure cloud. The insights and knowledge they share willhelp you find the right opportunities for AI in your organization and enableyou to get started. I’m inspired by Andreas and Michael’s work and how theylive Microsoft’s mission to empower every person and every organization onthe planet to achieve more.Ricardo Henriques, EMEA Lead - FastTrack for AzureAbout the reviewersArianna Olivelliis a marine scientist based in London. She is currentlyundertaking a Ph.D. in chemical oceanography. In the past, she has workedon numerical, statistical, and machine learning models focused on marine andriverine plastic pollution. In her free time, she loves to play sports and spendtime outdoors.Maria Vrabieis an engineer working in the FastTrack for Azure team withinthe Engineering organization at Microsoft. She is currently helping variousbusinesses implement Azure solutions focusing on Intelligent agents,Cognitive Services, as well as analytics. Community enthusiast and inclusionadvocate, she has been volunteering at different events throughout years. Inher spare time, she enjoys cycling and Latin dancing.

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Table of ContentsPreface

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Section 1: Starting your cloud-based datascience journey

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Chapter 1: An Overview of Modern DataScienceThe evolution of data scienceWorking on a data science projectUnderstanding of the business problemAcquiring and exploring the dataFeature engineeringTraining the modelDeploying the modelUsing Spark in data scienceAdopting the DevOps mindsetSummaryFurther reading

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Chapter 2: Deploying Azure MachineLearning Workspace ResourcesTechnical requirementsDeploying Azure ML through the portalUsing the deployment wizardDeploying Azure ML via the CLIDeploying Azure Cloud ShellUsing the Azure CLIInstalling the Azure ML CLI extensionDeploying Azure ML using the az ml commandCleaning up the CLI resource groupAlternative ways to deploy an Azure MLworkspaceExploring the deployed Azure resourcesUnderstanding Role-Based Access Control(RBAC)RBAC inheritanceCreating custom rolesAssigning roles in the Azure ML workspaceSummaryQuestions

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