Dennis Michael Sawyers - Automated Machine Learning with Microsoft Azure: Build highly accurate and scalable end-to-end AI solutions with Azure AutoML
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- Book:Automated Machine Learning with Microsoft Azure: Build highly accurate and scalable end-to-end AI solutions with Azure AutoML
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A practical, step-by-step guide to using Microsofts AutoML technology on the Azure Machine Learning service for developers and data scientists working with the Python programming language
Key Features- Create, deploy, productionalize, and scale automated machine learning solutions on Microsoft Azure
- Improve the accuracy of your ML models through automatic data featurization and model training
- Increase productivity in your organization by using artificial intelligence to solve common problems
Automated Machine Learning with Microsoft Azure helps you to build high-performing, accurate machine learning models in record time. It allows anyone to easily harness the power of artificial intelligence and increase the productivity and profitability of your business. With a series of clicks on a guided user interface (GUI), novices and seasoned data scientists alike can train and deploy machine learning solutions to production with ease.
This book will teach you how to use Azure AutoML with both the GUI as well as the AzureML Python software development kit (SDK) in a careful, step-by-step way. First, youll learn how to prepare data, train models, and register them to your Azure Machine Learning workspace. Youll then discover how to take those models and use them to create both automated batch solutions using machine learning pipelines and real-time scoring solutions using Azure Kubernetes Service (AKS). Finally, you will be able to use AutoML on your own data to not only train regression, classification, and forecasting models but also use them to solve a wide variety of business problems.
By the end of this Azure book, youll be able to show your business partners exactly how your ML models are making predictions through automatically generated charts and graphs, earning their trust and respect.
What you will learn- Understand how to train classification, regression, and forecasting ML algorithms with Azure AutoML
- Prepare data for Azure AutoML to ensure smooth model training and deployment
- Adjust AutoML configuration settings to make your models as accurate as possible
- Determine when to use a batch-scoring solution versus a real-time scoring solution
- Productionalize your AutoML solution with Azure Machine Learning pipelines
- Create real-time scoring solutions with AutoML and Azure Kubernetes Service
- Discover how to quickly deliver value and earn business trust using AutoML
- Train a large number of AutoML models at once using the AzureML Python SDK
Data scientists, aspiring data scientists, machine learning engineers, or anyone interested in applying artificial intelligence or machine learning in their business will find this book useful. You need to have beginner-level knowledge of artificial intelligence and a technical background in computer science, statistics, or information technology before getting started with this machine learning book. Familiarity with Python will help you implement this books more advanced features, but even data analysts and SQL experts will be able to train ML models after finishing this book.
Table of Contents- Introducing AutoML
- Getting Started with Azure Machine Learning Service
- Training Your First AutoML Model
- Building an AutoML Regression Solution
- Building an AutoML Classification Solution
- Building an AutoML Forecasting Solution
- Using the Many Models Solution Accelerator
- Choosing Real-Time versus Batch Scoring
- Implementing a Batch Scoring Solution
- Creating End-to-End AutoML Solutions
- Implementing a Real-Time Scoring Solution
- Realizing Business Value with AutoML
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Build highly accurate and scalable end-to-end AI solutions with Azure AutoML
Dennis Michael Sawyers
BIRMINGHAMMUMBAI
Copyright 2021 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
Group Product Manager: Kunal Parikh
Publishing Product Manager: Ali Abidi
Senior Editor: David Sugarman
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First published: April 2021
Production reference: 1260321
Published by Packt Publishing Ltd.
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ISBN 978-1-80056-531-9
www.packt.com
To my wife, Kyoko Sawyers, who has always been by my side and supported me through many long evenings, and to my daughter, Sophia Rose, who was born halfway through the writing of this book.
Dennis 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.
I want to thank the people who have been close to me and supported me, especially my wife, Kyoko, for encouraging me to finish this book, Rick Durham and Sam Istephan, for teaching me Azure Machine Learning, and Sabina Cartacio, Aniththa Umamahesan, and Deepti Mokkapati from the Microsoft Azure product team for helping me learn the ins and outs of AutoML.
Marek Chmel is a senior CSA at Microsoft, specializing in data and AI. He is a speaker and trainer with more than 15 years' experience. He has been a Data Platform MVP since 2012. He has earned numerous certifications, including Azure Architect, Data Engineer and Scientist Associate, Certified Ethical Hacker, and several eLearnSecurity certifications. Marek earned his master's degree in business and informatics from Nottingham Trent University. He started his career as a trainer for Microsoft Server courses and later worked as SharePoint team lead and principal database administrator. He has authored two books, Hands-On Data Science with SQL Server 2017 and SQL Server 2017 Administrator's Guide.
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