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Azure Data Scientist Associate Certification Guide. A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam Andreas Botsikas, Michael Hlobil

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Azure Data Scientist Associate Certification Guide. A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam Andreas Botsikas, Michael Hlobil - okladka książki

Azure Data Scientist Associate Certification Guide. A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam Andreas Botsikas, Michael Hlobil - okladka książki

Azure Data Scientist Associate Certification Guide. A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam Andreas Botsikas, Michael Hlobil - audiobook MP3

Azure Data Scientist Associate Certification Guide. A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam Andreas Botsikas, Michael Hlobil - audiobook CD

Autorzy:
Andreas Botsikas, Michael Hlobil
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
448
Dostępne formaty:
     PDF
     ePub
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.

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O autorach książki

Andreas Botsikas is an experienced advisor working in the software industry. He has worked in the finance sector, leading highly efficient DevOps teams, and architecting and building high-volume transactional systems. He then traveled the world, building AI-infused solutions with a group of engineers and data scientists. Currently, he works as a trusted advisor for customers onboarding into Azure, de-risking and accelerating their cloud journey. He is a strong engineering professional with a Doctor of Philosophy (Ph.D.) in resource optimization with artificial intelligence from the National Technical University of Athens.
Michael Hlobil is an experienced architect focused on quickly understanding customers' business needs, with over 25 years of experience in IT pitfalls and successful projects, and is dedicated to creating solutions based on the Microsoft 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 advanced analytics projects in the last decade, including massive parallel systems and Machine Learning systems. He enjoys working with customers and supporting the journey to the cloud.

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