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Azure Data Scientist Associate DP-100 Certification Guide. A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam - Second Edition Evangelos Misirlis

Język publikacji: angielski
Azure Data Scientist Associate DP-100 Certification Guide. A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam - Second Edition Evangelos Misirlis - okladka książki

Azure Data Scientist Associate DP-100 Certification Guide. A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam - Second Edition Evangelos Misirlis - okladka książki

Autor:
Evangelos Misirlis
Serie wydawnicze:
Practical
Ocena:
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 foundational concepts in data science, you'll learn how to configure and use the Azure Machine Learning (Azure ML) workspace via both studio and SDK interfaces. You'll progress through no-code and low-code experimentation using AutoML and the visual designer, and delve into advanced Python SDK-based model training and deployment.
This book also introduces you to the power of Generative AI with Prompt Flow, enabling you to build intelligent agents and operationalize them for production use. You’ll gain skills in hyperparameter tuning, model interpretation, and fairness analysis, and finally, deploy models as scalable endpoints with robust monitoring.
Complete with hands-on exercises, mock exams, and expert tips, this guide offers everything you need to tackle the DP-100 exam and apply your learnings in real-world data science scenarios.

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O autorze książki

Evangelos Misirlis is a Data and AI Solution Architect at CHUBB, with expertise in risk analytics and operational AI. A former Cloud Solution Architect at Microsoft, he holds a Master's in AI for Emotion Estimation and brings deep insight into real-world deployment of ML models in regulated industries.

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