No detailed description available for "Getting Started with Amazon SageMaker Studio".
Sprache
Verlagsort
Basel/Berlin/Boston
Großbritannien
Zielgruppe
Editions-Typ
Produkt-Hinweis
Dateigröße
ISBN-13
978-1-80107-348-6 (9781801073486)
Schweitzer Klassifikation
Hsieh Michael:
Michael Hsieh is a senior AI/machine learning (ML) solutions architect at Amazon Web Services. He creates and evangelizes for ML solutions centered around Amazon SageMaker. He also works with enterprise customers to advance their ML journeys. Prior to working at AWS, Michael was an advanced analytic consultant creating ML solutions and enterprise-level ML strategies at Slalom Consulting in Philadelphia, PA. Prior to consulting, he was a data scientist at the University of Pennsylvania Health System, focusing on personalized medicine and ML research. Michael has two master's degrees, one in applied physics and one in robotics. Originally from Taipei, Taiwan, Michael currently lives in Sammamish, WA, but still roots for the Philadelphia Eagles.
Table of Contents - Machine Learning and Its Life Cycle in the Cloud
- Introducing Amazon SageMaker Studio
- Data Preparation with SageMaker Data Wrangler
- Building a Feature Repository with SageMaker Feature Store
- Building and Training ML Models with SageMaker Studio IDE
- Detecting ML Bias and Explaining Models with SageMaker Clarify
- Hosting ML Models in the Cloud: Best Practices
- Jumpstarting ML with SageMaker JumpStart and Autopilot
- Training ML Models at Scale in SageMaker Studio
- Monitoring ML Models in Production with SageMaker Model Monitor
- Operationalize ML Projects with SageMaker Projects, Pipelines and Model Registry
