AWS Certified Machine Learning Study Guide. Shreyas Subramanian

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

      13  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

      14  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