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Azure Data Scientist Associate Certification Guide

You're reading from Azure Data Scientist Associate Certification Guide A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam

Product type Paperback

Published in Dec 2021

Publisher Packt

ISBN-13 9781800565005

Length 448 pages

Edition 1st Edition

Languages

Python

Tools

Azure

Concepts

Machine Learning

Authors (2):

Andreas Botsikas

Michael Hlobil

View More author details

Table of Contents (17) Chapters

Preface

1. Section 1: Starting your cloud-based data science journey

2. Chapter 1: An Overview of Modern Data Science FREE CHAPTER

3. Chapter 2: Deploying Azure Machine Learning Workspace Resources

4. Chapter 3: Azure Machine Learning Studio Components

5. Chapter 4: Configuring the Workspace

6. Section 2: No code data science experimentation

7. Chapter 5: Letting the Machines Do the Model Training

8. Chapter 6: Visual Model Training and Publishing

9. Section 3: Advanced data science tooling and capabilities

10. Chapter 7: The AzureML Python SDK

11. Chapter 8: Experimenting with Python Code

12. Chapter 9: Optimizing the ML Model

13. Chapter 10: Understanding Model Results

14. Chapter 11: Working with Pipelines

15. Chapter 12: Operationalizing Models with Code

16. Other Books You May Enjoy

Chapter 4: Configuring the Workspace

In this chapter, you will work inside the Azure Machine Learning (ML) Studio web interface and learn how to configure the infrastructure needed to run an experiment inside its workspace. Then, you will learn how to provision or attach to existing compute resources and establish the connection between the Azure ML workspace and the various datastores that host your data. With these resources configured, you will be able to register a dataset and explore the capabilities offered in Azure ML to monitor those datasets.

In this chapter, we're going to cover the following main topics:

Provisioning compute resources
Connecting to datastores
Working with datasets

The rest of the chapter is locked

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Authors (2)

Andreas Botsikas

Andreas Botsikas

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.

See other products by Andreas Botsikas

Hlobil

Hlobil

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.

See other products by Hlobil

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