Ali Arsanjani

Machine learning (ML) engineers and practitioners developing custom ML models on cloud technologies prefer to start from established guidelines rather than learning through trial and error. In this chalk talk, learn about the Machine Learning Lens for the AWS Well-Architected Framework, which provides an established, consistent, and repeatable set of best practices.

Amazon SageMaker offers purpose-built tools for the complete machine learning (ML) lifecycle to help data scientists and ML practitioners build, train, and deploy high-quality ML models quickly. In this session, learn how to use SageMaker for data labeling, data preparation, feature engineering, statistical bias detection, training, tuning, deployment, monitoring, MLOps, and human review.