AWS Certified Machine Learning Study Guide. Shreyas SubramanianЧитать онлайн книгу.
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
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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