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Azure Data Scientist Associate Certification Guide

You're reading from Azure Data Scientist Associate Certification Guide

Product type Book

Published in Dec 2021

Publisher Packt

ISBN-13 9781800565005

Pages 448 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Authors (2):

Andreas Botsikas

Michael Hlobil

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Table of Contents (17) Chapters

Preface

Section 1: Starting your cloud-based data science journey

Chapter 1: An Overview of Modern Data Science

Chapter 2: Deploying Azure Machine Learning Workspace Resources

Chapter 3: Azure Machine Learning Studio Components

Chapter 4: Configuring the Workspace

Section 2: No code data science experimentation

Chapter 5: Letting the Machines Do the Model Training

Chapter 6: Visual Model Training and Publishing

Section 3: Advanced data science tooling and capabilities

Chapter 7: The AzureML Python SDK

Chapter 8: Experimenting with Python Code

Chapter 9: Optimizing the ML Model

Chapter 10: Understanding Model Results

Chapter 11: Working with Pipelines

Chapter 12: Operationalizing Models with Code

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Overview of the Python SDK

The AzureML SDK is a Python library that allows you to interact with the AzureML services. It also provides you with data science modules that will assist you in your machine learning journey. The AzureML SDK is available in the R programming language through a Python to R interoperability package.

The SDK consists of several packages that group different types of modules you can import into your code base. All the Microsoft-supported modules are placed within packages that start with azureml, such as azureml.core and azureml.train.hyperdrive. The following diagram offers a broad overview of the AzureML SDK's most frequently used packages, as well as the key modules that you will see in this book and the exam:

Figure 7.1 – The AzureML SDK modules and important classes

Note that all the key classes that exist in the azureml.core package can also be imported from the corresponding child module. For example, the Experiment...

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Authors (2)

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.

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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.

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