Cloud native AI and machine learning on AWS : use SageMaker for building ML models, automate MLOps, and take advantage of numerous AWS AI services /
Rangarajan, Premkumar,
Cloud native AI and machine learning on AWS : use SageMaker for building ML models, automate MLOps, and take advantage of numerous AWS AI services / Premkumar Rangarajan, David Bounds. - 1st edition. - 400 pages : illustrations ; 24 cm.
Includes bibliographical references.
505 0\$a1. Introducing the ML Workflow ‡ 2. Hydrating the Data Lake ‡ 3. Predicting the Future With Features ‡ 4. Orchestrating the Data Continuum ‡ 5. Casting a Deeper Net (Algorithms and Neural Networks) ‡ 6. Iteration Makes Intelligence (Model Training and Tuning) ‡ 7. Let George Take Over (AutoML in Action) ‡ 8. Blue or Green (Model Deployment Strategies) ‡ 9. Wisdom at Scale with Elastic Inference ‡ 10. Adding Intelligence with Sensory Cognition ‡ 11. AI for Industrial Automation ‡ 12. Operationalized Model Assembly (MLOps and Best Practices).
This book guides data and cloud professionals to design, deploy, and manage end-to-end AI/ML systems on AWS using SageMaker, Comprehend, Rekognition, Lookout, and AutoML. It covers MLOps automation, neural networks, data lakes, operational best practices, and real-world case studies. :contentReference[oaicite:1]
9789355513267
Machine learning--Implementation.
Cloud computing.
006.3 / R.P.C
Cloud native AI and machine learning on AWS : use SageMaker for building ML models, automate MLOps, and take advantage of numerous AWS AI services / Premkumar Rangarajan, David Bounds. - 1st edition. - 400 pages : illustrations ; 24 cm.
Includes bibliographical references.
505 0\$a1. Introducing the ML Workflow ‡ 2. Hydrating the Data Lake ‡ 3. Predicting the Future With Features ‡ 4. Orchestrating the Data Continuum ‡ 5. Casting a Deeper Net (Algorithms and Neural Networks) ‡ 6. Iteration Makes Intelligence (Model Training and Tuning) ‡ 7. Let George Take Over (AutoML in Action) ‡ 8. Blue or Green (Model Deployment Strategies) ‡ 9. Wisdom at Scale with Elastic Inference ‡ 10. Adding Intelligence with Sensory Cognition ‡ 11. AI for Industrial Automation ‡ 12. Operationalized Model Assembly (MLOps and Best Practices).
This book guides data and cloud professionals to design, deploy, and manage end-to-end AI/ML systems on AWS using SageMaker, Comprehend, Rekognition, Lookout, and AutoML. It covers MLOps automation, neural networks, data lakes, operational best practices, and real-world case studies. :contentReference[oaicite:1]
9789355513267
Machine learning--Implementation.
Cloud computing.
006.3 / R.P.C