Optimizing Machine Learning Compute in Production with AWS SageMaker
In the rapidly evolving landscape of machine learning, efficient resource management is crucial for optimizing performance and controlling costs.
This talk will explore best practices and advanced strategies for optimizing machine learning compute in production environments using AWS SageMaker.
We will delve into key features such as SageMaker’s managed infrastructure, auto-scaling capabilities, and inference components. Attendees will gain insights into leveraging SageMaker’s integrated tools for model monitoring and automated scaling to enhance model performance and operational efficiency.
Tony Song
Senior Machine Learning Engineer, ML at Capital One
Tony Song is a motivated, creative, and innovative Machine Learning Engineer & Data Scientist, who focuses on Python, Machine Learning, and Data Science.
