AWS Certified Machine Learning Engineer Study Guide

ABOUT THE AUTHOR DARIO CABIANCA is the AWS Practice Director at Trace3—a leading IT consultancy and AWS Advanced Consulting Partner—offering AI, data, cloud and cybersecurity solutions. He is the author of Google Cloud Platform (GCP) Professional Cloud Security Engineer Certification Companion and Google Cloud Platform (GCP) Professional Cloud Network Engineer Certification Companion. Dario has collaborated with leading global consulting firms and enterprises for over 20 years, delivering impactful solutions in enterprise architecture, cloud computing, cybersecurity, and artificial intelligence.

• ContentsChapter 1Introduction to Machine Learning1Understanding Artificial Intelligence2Data, Information, Knowledge3Data3Information4Knowledge5Understanding Machine Learning6ML Lifecycle6Define ML Problem6Collect Data8Process Data8Choose Algorithm8Train Model9Evaluate Model9Deploy Model9Derive Inference11Monitor Model11ML Concepts11Features11Target Variable12Optimization Problem12Objective Function13ML Algorithms vs. ML Models13Differences Between ML and AI14Understanding Deep Learning16Introduction to Neural Networks16Structure of a Neural Network16Neuron16Input Layer18Hidden Layers18Output Layer18How Neural Networks Work18Neural Networks Types19Artificial Neural Networks20Deep Neural Networks20Convolutional Neural Networks20Recurrent Neural Networks20Differences Between DL and ML21Case Studies21Case Study 1: Mobileye’s Autonomous Driving Technology21Case Study 2: Leidos’ Healthcare ML Applications21Summary22Exam Essentials23Review Questions24Chapter 2Data Ingestion and Storage27Introducing Ingestion and Storage28Ingesting and Storing Data28Data Formats and Ingestion Techniques31Choosing AWS Ingestion Services34Amazon Data Firehose35Amazon Kinesis Data Streams35Amazon Managed Streaming for Apache Kafka (MSK)36Amazon Managed Service for Apache Flink38AWS DataSync39AWS Glue40Choosing AWS Storage Services41Amazon Simple Storage Service (S3)42Amazon Elastic File System (EFS)45Amazon FSx for Lustre47Amazon FSx for NetApp ONTAP49Amazon FSx for Windows File Server50Amazon FSx for OpenZFS51Amazon Elastic Block Storage (EBS)51Amazon Relational Database Service (RDS)52Amazon DynamoDB52Troubleshooting53Summary54Exam Essentials55Review Questions57Chapter 4Model Selection61Understanding AWS AI Services63Vision64Amazon Rekognition64Amazon Textract65Speech66Amazon Polly66Amazon Transcribe67Language67Amazon Translate67Amazon Comprehend68Chatbot69Amazon Lex69Recommendation70Amazon Personalize70Generative AI71Amazon Bedrock71Developing Models with Amazon SageMaker Built-in Algorithms81Supervised ML Algorithms81General Regression and Classification Algorithms83Recommendation102Forecasting104Unsupervised ML Algorithms105Clustering105Dimensionality Reduction113Topic Modeling119Anomaly Detection121Textual Analysis123BlazingText124Sequence-to-Sequence126Image Processing127Image Classification127Object Detection128Semantic Segmentation130Criteria for Model Selection131Summary132Exam Essentials133Review Questions136Chapter 5Model Training and Evaluation141Training143Local Training144Remote Training145Distributed Training146Monitoring Training Jobs147Debugging Training Jobs148Hyperparameter Tuning149Model Parameter and Hyperparameter151Exploring the Hyperparameter Space with Amazon SageMaker AI Automatic Model Tuning152Evaluation Metrics154Classification Problem Metrics154Regression Problem Metrics160Hyperparameter Tuning Techniques164Manual Search164Grid Search165Random Search165Bayesian Search165Multi-algorithm Optimization166Managing Bias and Variance Trade-Off166Addressing Overfitting and Underfitting168Underfitting168Overfitting170Regularization170Advanced Techniques173Model Performance Evaluation173Performance Evaluation Methods173K-Fold Cross-Validation174Random Train-Test Split175Holdout Set176Bootstrap176Evaluating Foundation Models177Automatic Evaluations177Human Evaluations177LLM-as-a-Judge177Programmatic Evaluations177Knowledge Base Evaluations177Deep Dive Model Tuning Example177Summary185Exam Essentials187Review Questions190Chapter 6Model Deployment and Orchestration193AWS Model Deployment Services194Deploying AI Services195Amazon Rekognition196Amazon Textract197Amazon Polly197Amazon Transcribe198Amazon Comprehend198Amazon Lex199Amazon Personalize199Amazon Bedrock200Deploying Your Model201Infrastructure Selection Considerations202Managed Model Deployments203Unmanaged Model Deployments211Optimizing ML Models for Edge Devices216Advanced Model Deployment Techniques218Autoscaling Endpoints218Deployment and Testing Strategies221Blue/Green Deployment221Orchestrating ML Workflows227Introducing Amazon SageMaker Pipelines228Code Repository and Version Control228Introducing Amazon SageMaker Model Registry229CI/CD230MLOps Orchestration230AWS Step Functions231Amazon Managed Workflows for Apache Airflow232Choosing an Orchestration Tool232Automating Model Building and Deployment233Define the Workflow Steps234Create and Configure Pipeline Steps234Define the Pipeline237Set Up Triggers and Schedules237Execute the Pipeline238Key Considerations238Deep-Dive Model Deployment Example238Summary247Exam Essentials248Review Questions250Chapter 7Model Monitoring and Cost Optimization253Monitoring Model Inference255Drifts in Models256Techniques to Monitor Data Quality and Model Performance257Monitoring Workflow259Design Principles for Monitoring261Operational Excellence Pillar261Security Pillar262Reliability Pillar263Performance Efficiency Pillar264Cost Optimization Pillar266Sustainability Pillar269Monitoring Infrastructure and Cost270Monitoring and Observability Services271Amazon CloudWatch Logs Insights272Amazon EventBridge273AWS CloudTrail274AWS X-Ray274Amazon GuardDuty275Amazon Inspector276AWS Security Hub277Cost Tracking and Optimization Services278AWS Cost Explorer278AWS Cost and Usage Reports279AWS Trusted Advisor280AWS Budgets280Pricing Models281Summary283Exam Essentials284Review Questions286Chapter 8Model Security289Security Design Principles290Implement a Strong Identity Foundation290Apply Security at all Layers291Enable Traceability292Protect Your Data (At-Rest, In-Use, and In-Transit)293Automate Security Processes294Prepare for Security Events295Securing AWS Services295Securing Identities with IAM296Identities296Access Policies302Securing Infrastructure and Data305Network Isolation with VPC305Private Connectivity306Data Protection306Monitoring and Auditing307Ensuring Compliance307Summary308Exam Essentials309Review Questions311