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AWS Certified Machine Learning Study Guide

Specialty (MLS-C01) Exam
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Book Hero Magic crafted this summary to help describe this book. While it's new and still learning, it may not be perfect - your feedback is welcome! Summary
AWS Certified Machine Learning Study Guide is a comprehensive resource for anyone preparing for the AWS Certified Machine Learning – Specialty exam. The book covers essential machine learning topics and practical applications within AWS services. Through detailed explanations and example scenarios, it helps readers understand key concepts and methodologies necessary for the certification.
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Format: Paperback / softback
$11499
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Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?

This book may appeal to you if you're looking to develop your expertise in AWS machine learning services. It's ideal for those seeking to enhance their understanding of machine learning concepts and practical applications using AWS, as well as for professionals aiming to pass the associated certification exam.

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The AWS Certified Machine Learning Study Guide is your one-stop resource for complete coverage of the Specialty MLS-C01 certification exam.The Sybex study guide covers 100% of the MLS-C01 domain competencies.

Book Hero Magic formatted this description to make it easier to read. While it's new and still learning, it may not be perfect - your feedback is welcome! Description

Succeed on the AWS Machine Learning exam or in your next job as a machine learning specialist on the AWS Cloud platform with this hands-on guide.

As the most popular cloud service in the world today, Amazon Web Services offers a wide range of opportunities for those interested in developing and deploying artificial intelligence and machine learning business solutions.

AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam delivers hyper-focused, authoritative instruction for anyone pursuing the prestigious Amazon Web Services Machine Learning certification or a new career as a machine learning specialist within the AWS architecture.

From exam to interview to your first day on the job, this study guide provides the domain-by-domain specific knowledge you need to build, train, tune, and deploy machine learning models with the AWS Cloud. The practice exams and assessments, electronic flashcards, and supplementary online resources that accompany this Study Guide ensure you're prepared for success in every subject area covered by the exam.

You’ll also find:

  • An intuitive and organised layout perfect for anyone taking the exam for the first time or seasoned professionals seeking a refresher on machine learning on the AWS Cloud.
  • Authoritative instruction on a widely recognised certification that unlocks countless career opportunities in machine learning and data science.
  • Access to the Sybex online learning resources and test bank, with chapter review questions, a full-length practice exam, hundreds of electronic flashcards, and a glossary of key terms.

AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam is an indispensable guide for anyone seeking to prepare for success on the AWS Certified Machine Learning Specialty exam, a job interview in the field of machine learning, or wishing to improve their skills as they pursue a career in AWS machine learning.

Book Details

INFORMATION

ISBN: 9781119821007

Publisher: John Wiley & Sons Inc

Format: Paperback / softback

Date Published: 07 February 2022

Country: United States

Imprint: Sybex Inc.,U.S.

Audience: Professional and scholarly

DIMENSIONS

Spine width: 23.0mm

Width: 185.0mm

Height: 231.0mm

Weight: 476g

Pages: 352

About the Author

ABOUT THE AUTHORs

Shreyas Subramanian, PhD, is Principal Machine Learning specialist at Amazon Web Services. He has worked with several enterprise companies on business-critical machine learning and optimization problems.

Stefan Natu is Principal Machine Learning Specialist at Alexa AI, prior to which he was a Principal Architect at Amazon Web Services. His professional focus is on financial services, and he helps customers architect ML use cases on AWS with an emphasis on security, enterprise model governance, and operationalizing machine learning models.

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