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You're reading from  Azure Data Scientist Associate Certification Guide

Product typeBook
Published inDec 2021
Reading LevelBeginner
PublisherPackt
ISBN-139781800565005
Edition1st Edition
Languages
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Authors (2):
Andreas Botsikas
Andreas Botsikas
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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
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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

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Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "You can also change the autogenerated name of the pipeline you are designing. Rename the current pipeline to test-pipeline."

A block of code is set as follows:

from azureml.train.hyperdrive import GridParameterSampling
from azureml.train.hyperdrive import choice
param_sampling = GridParameterSampling( {
        "a": choice(0.01, 0.5),
        "b": choice(10, 100)
    }
)

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

from azureml.core import Workspace
ws = Workspace.from_config()
loans_ds = ws.datasets['loans']
compute_target = ws.compute_targets['cpu-sm-cluster']

Any command-line input or output is written as follows:

az group create --name my-name-rg --location westeurope

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: "Navigate to the Author | Notebooks section of your AzureML Studio web interface."

Tips or important notes

Run numbers may be different in your executions. Every time you execute the cells, a new run number is created, continuing from the previous number. So, if you execute code that performs one hyperdrive run with 20 child runs, the last child run will be run 21. The next time you execute the same code, the hyperdrive run will start from run 22, and the last child will be run 42. The run numbers referred to in this section are the ones shown in the various figures, and it is normal to observe differences, especially if you had to rerun a couple of cells.

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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