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Azure Data Scientist Associate Certification Guide
Azure Data Scientist Associate Certification Guide

Azure Data Scientist Associate Certification Guide: A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam

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Profile Icon Andreas Botsikas Profile Icon Hlobil
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AU$24.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (11 Ratings)
Paperback Dec 2021 448 pages 1st Edition
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AU$53.99 AU$60.99
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AU$75.99
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Renews at AU$24.99p/m
Arrow left icon
Profile Icon Andreas Botsikas Profile Icon Hlobil
Arrow right icon
AU$24.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (11 Ratings)
Paperback Dec 2021 448 pages 1st Edition
eBook
AU$53.99 AU$60.99
Paperback
AU$75.99
Subscription
Free Trial
Renews at AU$24.99p/m
eBook
AU$53.99 AU$60.99
Paperback
AU$75.99
Subscription
Free Trial
Renews at AU$24.99p/m

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Table of content icon View table of contents Preview book icon Preview Book

Azure Data Scientist Associate Certification Guide

Section 1: Starting your cloud-based data science journey

An Azure Data Scientist Associate is a subject matter expert with applied data science and machine learning knowledge, able to run machine learning workloads on Azure. The responsibilities for this role include planning and creating a suitable working environment for data science workloads on Azure. In this section, you will get an overview of the data science and machine learning terminology used throughout the book. You will also learn how to provision and configure the Azure Machine Learning services, the de facto environment for running machine learning experiments in the Azure cloud.

This section comprises of the following chapters:

  • Chapter 1, An Overview of Modern Data Science
  • Chapter 2, Deploying Azure Machine Learning Workspace Resources
  • Chapter 3, Azure Machine Learning Studio Components
  • Chapter 4, Configuring the Workspace
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Key benefits

  • Create end-to-end machine learning training pipelines, with or without code
  • Track experiment progress using the cloud-based MLflow-compatible process of Azure ML services
  • Operationalize your machine learning models by creating batch and real-time endpoints

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.

Who is this book 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.

What you will learn

  • Create a working environment for data science workloads on Azure
  • Run data experiments using Azure Machine Learning services
  • Create training and inference pipelines using the designer or code
  • Discover the best model for your dataset using Automated ML
  • Use hyperparameter tuning to optimize trained models
  • Deploy, use, and monitor models in production
  • Interpret the predictions of a trained model

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Dec 03, 2021
Length: 448 pages
Edition : 1st
Language : English
ISBN-13 : 9781800565005
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Product Details

Publication date : Dec 03, 2021
Length: 448 pages
Edition : 1st
Language : English
ISBN-13 : 9781800565005
Category :
Languages :
Tools :

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Frequently bought together


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Table of Contents

16 Chapters
Section 1: Starting your cloud-based data science journey Chevron down icon Chevron up icon
Chapter 1: An Overview of Modern Data Science Chevron down icon Chevron up icon
Chapter 2: Deploying Azure Machine Learning Workspace Resources Chevron down icon Chevron up icon
Chapter 3: Azure Machine Learning Studio Components Chevron down icon Chevron up icon
Chapter 4: Configuring the Workspace Chevron down icon Chevron up icon
Section 2: No code data science experimentation Chevron down icon Chevron up icon
Chapter 5: Letting the Machines Do the Model Training Chevron down icon Chevron up icon
Chapter 6: Visual Model Training and Publishing Chevron down icon Chevron up icon
Section 3: Advanced data science tooling and capabilities Chevron down icon Chevron up icon
Chapter 7: The AzureML Python SDK Chevron down icon Chevron up icon
Chapter 8: Experimenting with Python Code Chevron down icon Chevron up icon
Chapter 9: Optimizing the ML Model Chevron down icon Chevron up icon
Chapter 10: Understanding Model Results Chevron down icon Chevron up icon
Chapter 11: Working with Pipelines Chevron down icon Chevron up icon
Chapter 12: Operationalizing Models with Code Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5
(11 Ratings)
5 star 63.6%
4 star 27.3%
3 star 9.1%
2 star 0%
1 star 0%
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prashant dhanavade Jul 18, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Excellent content. Covers all exam topics.
Amazon Verified review Amazon
Om S Dec 21, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
“Azure Data Scientist Associate Certification Guide”: for Microsoft Certified DP-100 exam - The content in the book is prodigious, and the authors have tried to compile all the important DP-100 ML exams-related topics in a medium-sized book.This book contains relevant hands-on exercises which are easy to follow along and implement with a visual interface, not only The order of the content topics is extremely good as well.This book covers advanced topics that are required for certification, so prior knowledge of the Azure cloud and basic ML knowledge is a bonus and makes learning easy.Each chapter has questions and references to “Further reading” which complement the exam topic, which is extremely helpful. The book starts from very basic topics and goes to advance topics as exams require to have an understanding of many topics, starting from overview, understanding Azure ML Studio, AutoML, Spark, Deployment, pipeline batch processing, real-time inference, analyzing model error, AzureML SDK, etc. I found the way topics are explained is fascinating. I would recommend it to anyone who is willing to pass the DP-100 exam and “get hands-on “ in MS Azure ml cloud platform. My recommendation would be to add more questions with answers for practice, this would add more value to the book.
Amazon Verified review Amazon
kio Dec 13, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I have been working with Andreas Botsikas, Michael Hlobil for more than 2 years now. As a category lead for FastTrack AI team, Andreas is instrumental on how we help our customers with AI solutions on a daily basis. His depth with Azure ML is such that for any ML question, my go to person is Andreas, he is my mentor. This book reflects the knee-deep expertise from Andreas and Michael. I recommend every professional, wanting to get up to speed with Azure ML, to take the journey with Andreas and Michael, as they take us through the core concepts of Azure ML, with examples, so you can become successful operationalizing your ML solution with Azure ML.
Amazon Verified review Amazon
alejandro Nov 22, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book helped me practice and get ready for the certification exam. I recommend until Microsoft rolls out their Python SDK upgrade. After that happens, the book would need to be updated.
Amazon Verified review Amazon
Amazon Kunde Oct 20, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I really love the book! It covers a lot of details about Azure ML. It's well written and also very fun to work through! I can recommend it for everyone who wants to get into Azure ML
Amazon Verified review Amazon
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