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Automated Machine Learning with Microsoft Azure

You're reading from Automated Machine Learning with Microsoft Azure

Product type Book

Published in Apr 2021

Publisher Packt

ISBN-13 9781800565319

Pages 340 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Dennis Michael Sawyers

Table of Contents (17) Chapters

Preface

Section 1: AutoML Explained – Why, What, and How

Chapter 1: Introducing AutoML

Chapter 2: Getting Started with Azure Machine Learning Service

Chapter 3: Training Your First AutoML Model

Section 2: AutoML for Regression, Classification, and Forecasting – A Step-by-Step Guide

Chapter 4: Building an AutoML Regression Solution

Chapter 5: Building an AutoML Classification Solution

Chapter 6: Building an AutoML Forecasting Solution

Chapter 7: Using the Many Models Solution Accelerator

Section 3: AutoML in Production – Automating Real-Time and Batch Scoring Solutions

Chapter 8: Choosing Real-Time versus Batch Scoring

Chapter 9: Implementing a Batch Scoring Solution

Chapter 10: Creating End-to-End AutoML Solutions

Chapter 11: Implementing a Real-Time Scoring Solution

Chapter 12: Realizing Business Value with AutoML

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Transferring data using ADF

Moving data from on-premise to the cloud and from the cloud to on-premise is a key skill for any data engineer or data scientist. ADF accomplishes this task with the Copy data activity. This is ADF's most basic and most powerful function.

In this section, first, you will download a self-hosted integration runtime (SHIR) to your local machine, allowing your computer to serve as a compute resource to load data into Azure. Then, you will create a linked service for your Azure storage account and your local PC.

Next, you will download a file from the GitHub repository and save it to your PC. Finally, you will create a Copy data activity in ADF that will take data from your PC and put it into the same Azure blob container that's connected to your AML datastore.

Going through these exercises will give you the data engineering skills that will allow you to create an end-to-end solution in the next section.

Installing a self-hosted integration...

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Authors (1)

Dennis Michael Sawyers

Dennis Michael Sawyers is a senior cloud solutions architect (CSA) at Microsoft, specializing in data and AI. In his role as a CSA, he helps Fortune 500 companies leverage Microsoft Azure cloud technology to build top-class machine learning and AI solutions. Prior to his role at Microsoft, he was a data scientist at Ford Motor Company in Global Data Insight and Analytics (GDIA) and a researcher in anomaly detection at the highly regarded Carnegie Mellon Auton Lab. He received a master's degree in data analytics from Carnegie Mellon's Heinz College and a bachelor's degree from the University of Michigan. More than anything, Dennis is passionate about democratizing AI solutions through automated machine learning technology.

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