Amazon SageMaker Feature Store is a purpose-built solution for machine learning (ML) feature management. It helps data science teams reuse ML features across teams and models, serves features for model predictions at scale with low latency, and train and deploy new models more quickly and effectively.
As you learn about how to use a feature store, you may come across many examples that use very simple scenarios involving a few hundred or a few thousand rows of feature data. Although those examples help you get started, they don’t answer the question of what happens when your feature groups need …
Scale ML feature ingestion using Amazon SageMaker Feature Store
"The Power of AI in Business and Entrepreneurship: Unlocking Opportunities and Driving Success"
"The Power of AI: Revolutionizing Business and Empowering Entrepreneurs"
Optimize your inference jobs using dynamic batch inference with TorchServe on Amazon SageMaker
Graph-based recommendation system with Neptune ML: An illustration on social network link prediction...