Reader small image

You're reading from  Azure Data Scientist Associate Certification Guide

Product typeBook
Published inDec 2021
Reading LevelBeginner
PublisherPackt
ISBN-139781800565005
Edition1st Edition
Languages
Right arrow
Authors (2):
Andreas Botsikas
Andreas Botsikas
author image
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.
Read more about Andreas Botsikas

Michael Hlobil
Michael Hlobil
author image
Michael 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.
Read more about Michael Hlobil

View More author details
Right arrow

Summary

In this chapter, you learned how the AzureML Python SDK is structured. You also discovered the AzureML notebook editor, which allows you to code Python scripts. You then worked with the SDK. You started your coding journey by managing the compute targets that are attached to the AzureML workspace. You then attached new datastores and got a reference to existing ones, including the default datastore for the workspace. Then, you worked with various files and tabular-based datasets and learned how to reuse them by registering them in the workspace.

Finally, you worked with the AzureML CLI extension, which is a client that utilizes the Python SDK you explored in this chapter.

In the next chapter, you will build on top of this knowledge and learn how to use the AzureML SDK during the data science experimentation phase. You will also learn how to track metrics on your data science experiments, as well as how to scale your training into bigger computes, by running scripts in...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Azure Data Scientist Associate Certification Guide
Published in: Dec 2021Publisher: PacktISBN-13: 9781800565005

Authors (2)

author image
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.
Read more about Andreas Botsikas

author image
Michael 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.
Read more about Michael Hlobil