Sitting on mountains of data in Snowflake but struggling to turn it into predictions? This guide walks you through setting up a no-code ML workflow using Amazon SageMaker Canvas and Amazon QuickSight, so healthcare and retail teams can build fraud detection models without touching a single line of code.
source: [aws/machine-learning-blog]
Learn how to connect Amazon SageMaker Canvas to Snowflake, wrangle transaction data visually, and train an XGBoost fraud detection model—no coding required. This no-code approach lets you prepare data with Data Wrangler and build production-ready models, setting the stage for interactive dashboards.
source: [aws/machine-learning-blog]
Learn how to visualize fraud detection predictions from Amazon SageMaker Canvas in Amazon QuickSight with interactive dashboards and generative BI. This no-code workflow lets you ask questions in natural language and auto-generate executive summaries for your stakeholders.
source: [aws/machine-learning-blog]