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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Develop the skills you need to run machine learning workloads in Azure and pass the DP-100 exam with ease
Key Features:
Create 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 endpoints
Book 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 Learn:
Create 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 model
Who 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.
Publisher : Packt Publishing (December 3, 2021)
Language : English
Paperback : 448 pages
ISBN-10 : 1800565003
ISBN-13 : 978-1800565005
Item Weight : 1.72 pounds
Dimensions : 9.25 x 7.5 x 0.93 inches
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9 reviews for 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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prashant dhanavade –
Excellent and well organized
Excellent content. Covers all exam topics.
alejandro –
Great book to pass certification
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.
Amit Parulekar –
Content outline
Relevant and well organized content for the DP-100
Om S –
Great resource for Passing Microsoft Certified DP-100 exam
âAzure Data Scientist Associate Certification Guideâ: 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 âFurther readingâ 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 âget hands-on â 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.
kio –
Great book to learn Azure ML well and pass DP-100 exam for sure.
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.
Josh Luedeman –
Great certification readiness resource
This book is a great resource for anyone looking to prep for, and pass, the DP 100 exam. The explanations are well thought out and straightforward, and the repository of follow-on material is invaluable. I recommend this resource for anyone looking at attempting this exam.
Pranav Jain –
Innovative book to prepare for Azure Data Science Certification
I found this book to have a very interesting and innovative way of presenting all the topics needed to prepare for Azure Data Science Associate Certification. I’ve worked on Azure cloud technologies for last 3yrs and have an intermediate knowledge so I wanted to improve my overall knowledge and also prepare for the Certification hence I chose this book as it has a very detailed & easy way of explaining all the complex topics like Visual ML Model training, Optimization of Model, Understanding Model Results & Creating AzureML Pipelines. They also provide lots of code snippets and examples for better understanding and the only thing I found missing was how we can deploy these various models in a Production environment with CI/CD capabilities hence I would rate this a 4/5.
Patrick Hagan –
Screenshots are very small and hard to read.
Some of the Screenshots were OK and I could read the image. Most of them were very small. Even when I expanded the Image, the typing on the Image was still a very small Font.
Amazon Kunde –
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