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Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 2: Data preparation and model building with Amazon SageMaker Canvas

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In Part 2 of this no-code ML series, you connect Amazon SageMaker Canvas to Snowflake, prepare and join transaction data with Data Wrangler visual transformations, and train an XGBoost fraud detection model. All without writing machine learning code, laying the groundwork for interactive dashboards in Part 3.

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Part 1 covered the Snowflake database setup and established the foundational infrastructure for this no-code machine learning (ML) workflow. Part 2 of this blog series covers complete data preparation and model building workflow using Amazon SageMaker Canvas, demonstrating how to connect directly to Snowflake data sources, transform and prepare data using Data Wrangler’s visual transformations, and build a fraud detection model using the XGBoost algorithm. Amazon SageMaker Canvas is a visual,…

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Build a no-code ML workflow with Snowflake, Amazon SageMaker…