Practical decision-making using no-code ML

Organizations everywhere are using machine learning (ML) to accurately predict outcomes and make faster business decisions. To help more people use ML, Amazon SageMaker Canvas gives business analysts a no-code interface to make ML predictions on their own without requiring any ML experience. In this session, you will learn how to use SageMaker Canvas for top-use cases across sales, marketing, finance, and operations. We step through how to access and combine data from a variety of sources, automatically clean data, build ML models to generate predictions with a single click, and share models with others in your organization to improve productivity.

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Deploy ML models for inference at high performance and low cost
Deploy ML models for inference at high performance and low cost

High-performance, cost-effective model deployment is critical to ML return on investment. In this session, ...

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Transform genomic and biological data into insights
Transform genomic and biological data into insights

In this session, hear how Amazon Omics supports large-scale health and life science analysis and collaborat...