This repositiry contains Sagemaker componets and services that perform the following tasks:
• Ingest, register, and explore datasets
• Detect statistical bias in a dataset
• Automatically train and select models with AutoML
• Create machine learning features from raw data
• Save and manage features in a feature store
• Train and evaluate models using built-in algorithms and custom BERT models
• Debug, profile, and compare models to improve performance
• Build and run a complete ML pipeline end-to-end
• Optimize model performance using hyperparameter tuning
• Deploy and monitor models
• Perform data labeling at scale
• Build a human-in-the-loop pipeline to improve model performance
• Reduce cost and improve performance of data products