AWS Certified Machine Learning Study Guide: Specialty (MLS-C01) Exam
- Length: 352 pages
- Edition: 1
- Language: English
- Publisher: Sybex
- Publication Date: 2021-12-29
- ISBN-10: 1119821002
- ISBN-13: 9781119821007
- Sales Rank: #728128 (See Top 100 Books)
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 the development and deployment of artificial intelligence and machine learning business solutions.
The AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam delivers hyper-focused, authoritative instruction for anyone considering the pursuit of the prestigious Amazon Web Services Machine Learning certification or a new career as a machine learning specialist working 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. And with the practice exams and assessments, electronic flashcards, and supplementary online resources that accompany this Study Guide, you’ll be prepared for success in every subject area covered by the exam.
You’ll also find:
- An intuitive and organized 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 recognized 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 themselves for success on the AWS Certified Machine Learning Specialty exam or for a 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.
Cover Table of Contents Title Page Copyright Dedication Acknowledgments About the Authors About the Technical Editor Introduction The AWS Certified Machine Learning Specialty Exam Who Should Buy This Book Study Guide Features AWS Certified Machine Learning Specialty Exam Objectives Assessment Test Answers to Assessment Test PART I: Introduction Chapter 1: AWS AI ML Stack Amazon Rekognition Amazon Textract Amazon Transcribe Amazon Translate Amazon Polly Amazon Lex Amazon Kendra Amazon Personalize Amazon Forecast Amazon Comprehend Amazon CodeGuru Amazon Augmented AI Amazon SageMaker AWS Machine Learning Devices Summary Exam Essentials Review Questions Chapter 2: Supporting Services from the AWS Stack Storage Amazon VPC AWS Lambda AWS Step Functions AWS RoboMaker Summary Exam Essentials Review Questions PART II: Phases of Machine Learning Workloads Chapter 3: Business Understanding Phases of ML Workloads Business Problem Identification Summary Exam Essentials Review Questions Chapter 4: Framing a Machine Learning Problem ML Problem Framing Recommended Practices Summary Exam Essentials Review Questions Chapter 5: Data Collection Basic Data Concepts Data Repositories Data Migration to AWS Summary Exam Essentials Review Questions Chapter 6: Data Preparation Data Preparation Tools Summary Exam Essentials Review Questions Chapter 7: Feature Engineering Feature Engineering Concepts Feature Engineering Tools on AWS Summary Exam Essentials Review Questions Chapter 8: Model Training Common ML Algorithms Local Training and Testing Remote Training Distributed Training Monitoring Training Jobs Debugging Training Jobs Hyperparameter Optimization Summary Exam Essentials Review Questions Chapter 9: Model Evaluation Experiment Management Metrics and Visualization Summary Exam Essentials Review Questions Chapter 10: Model Deployment and Inference Deployment for AI Services Deployment for Amazon SageMaker Advanced Deployment Topics Summary Exam Essentials Review Questions Chapter 11: Application Integration Integration with On-Premises Systems Integration with Cloud Systems Integration with Front-End Systems Summary Exam Essentials Review Questions PART III: Machine Learning Well-Architected Lens Chapter 12: Operational Excellence Pillar for ML Operational Excellence on AWS Summary Exam Essentials Review Questions Chapter 13: Security Pillar Security and AWS Secure SageMaker Environments AI Services Security Summary Exam Essentials Review Questions Chapter 14: Reliability Pillar Reliability on AWS Change Management for ML Failure Management for ML Summary Exam Essentials Review Questions Chapter 15: Performance Efficiency Pillar for ML Performance Efficiency for ML on AWS Summary Exam Essentials Review Questions Chapter 16: Cost Optimization Pillar for ML Common Design Principles Cost Optimization for ML Workloads Summary Exam Essentials Review Questions Chapter 17: Recent Updates in the AWS AI/ML Stack New Services and Features Related to AI Services New Features Related to Amazon SageMaker Summary Exam Essentials Appendix Answers to the Review Questions Chapter 1: AWS AI ML Stack Chapter 2: Supporting Services from the AWS Stack Chapter 3: Business Understanding Chapter 4: Framing a Machine Learning Problem Chapter 5: Data Collection Chapter 6: Data Preparation Chapter 7: Feature Engineering Chapter 8: Model Training Chapter 9: Model Evaluation Chapter 10: Model Deployment and Inference Chapter 11: Application Integration Chapter 12: Operational Excellence Pillar for ML Chapter 13: Security Pillar Chapter 14: Reliability Pillar Chapter 15: Performance Efficiency Pillar for ML Chapter 16: Cost Optimization Pillar for ML Index End User License Agreement
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