
AWS Certified Machine Learning Study Guide
Specialty (MLS-C01) Exam
- English
- PDF
- Available on iOS & Android
About this book
Succeed on the AWS Machine Learning exam orinyour next jobas amachine learningspecialiston the AWSCloud platformwith this hands-on guide
As the most popular cloud servicein the world today, Amazon Web Services offers a wide range of opportunities for those interested in the development and deployment of artificial intelligence and machine learningbusinesssolutions.
The AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam delivershyper-focused, authoritative instruction for anyone considering the pursuit of theprestigious Amazon Web Services Machine Learning certification or a new career as a machine learning specialistworking within the AWS architecture.
From exam to interview to your first day on the job, this study guide provides the domain-by-domainspecific knowledge you need to build, train, tune, and deploy machine learning models with the AWSCloud. And with the practice exams and assessments, electronic flashcards, and supplementary online resourcesthataccompany this Study Guide, you'll be prepared for successin every subject area covered by the exam.
You'll also find:
- An intuitive and organized layout perfect foranyone taking the exam for the first time or seasoned professionals seeking a refresher on machine learningonthe AWSCloud
- Authoritative instruction on a widely recognized certification that unlocks countless career opportunities in machine learning and data science
- AccesstotheSybexonline learningresourcesand test bank, with chapter review questions, afull-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 foranyone seeking to prepare themselves for success on the AWS Certified Machine Learning Specialty examorfora job interview in the field of machine learning, or who wishes to improve their skills in the field as they pursue a career in AWS machine learning.
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Information
Table of contents
- Cover
- Title Page
- Copyright Page
- Acknowledgments
- About theĀ Authors
- About theĀ Technical Editor
- Contents at a Glance
- Contents
- Introduction
- Part I Introduction
- Part II Phases ofĀ Machine Learning Workloads
- Part III Machine Learning Well-Architected Lens
- Appendix Answers to the Review Questions
- Index
- EULA