Michael Hsieh - Getting Started with Amazon SageMaker Studio: Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE

Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE

Michael Hsieh

BIRMINGHAMMUMBAI

Getting Started with Amazon SageMaker Studio

Copyright 2022 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.

Publishing Product Manager: Dhruv Jagdish Kataria

Senior Editor: David Sugarman

Content Development Editor: Priyanka Soam

Technical Editor: Devanshi Ayare

Copy Editor: Safis Editing

Project Coordinator: Aparna Ravikumar Nair

Proofreader: Safis Editing

Indexer: Pratik Shirodkar

Production Designer: Roshan Kawale

Marketing Coordinators: Abeer Riyaz Dawe, Shifa Ansari

First published: March 2022

Production reference: 1240222

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham

B3 2PB, UK.

ISBN 978-1-80107-015-7

www.packt.com

This is for my wife, and my parents. Thank you for unconditionally supporting me and being there for me.

Michael Hsieh is a senior AI/machine learning (ML) solutions architect at Amazon Web Services. He creates and evangelizes for ML solutions centered around Amazon SageMaker. He also works with enterprise customers to advance their ML journeys.

Prior to working at AWS, Michael was an advanced analytic consultant creating ML solutions and enterprise-level ML strategies at Slalom Consulting in Philadelphia, PA. Prior to consulting, he was a data scientist at the University of Pennsylvania Health System, focusing on personalized medicine and ML research.

Michael has two master's degrees, one in applied physics and one in robotics.

Originally from Taipei, Taiwan, Michael currently lives in Sammamish, WA, but still roots for the Philadelphia Eagles.

Brent Rabowsky is a principal data science consultant at AWS with over 10 years' experience in the field of ML. At AWS, he leverages his expertise to help AWS customers with their data science projects. Prior to AWS, he joined Amazon.com on an ML and algorithms team, and he has previously worked on conversational AI agents for a government contractor and a research institute. He also served as a technical reviewer of the books Data Science on AWS by Chris Fregly and Antje Barth, published by O'Reilly, and SageMaker Best Practices and Learn Amazon SageMaker, published by Packt.

Ankit Sirmorya is an ML lead/senior ML engineer at Amazon and has led several machine-learning initiatives across the Amazon ecosystem. Ankit works on applying ML to solve ambiguous business problems and improve customer experience. For instance, he created a platform for experimenting with different hypotheses on Amazon product pages using reinforcement learning techniques. Currently, he works in the Alexa Shopping organization, where he is developing ML-based solutions to send personalized reorder hints to customers for improving their experience.