Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 1: Setting up your Snowflake environment
（翻译）使用Snowflake、Amazon SageMaker Canvas和Amazon Quick构建无代码机器学习工作流——第1部分：设置Snowflake环境
资讯摘要
Healthcare, retail, and life sciences teams store large volumes of operational data in Snowflake, but turning it into predictions is hard. In Part 1 of this series, you set up your AWS account and Snowflake environment for a no-code ML workflow with Amazon SageMaker Canvas, laying the foundation for
AI 摘要
本文是系列教程的第一部分，介绍如何为无代码机器学习工作流配置AWS账户和Snowflake环境。内容包括创建Snowflake数据库和仓库、生成欺诈检测示例数据，并验证数据，为后续使用Amazon SageMaker Canvas构建模型和Amazon QuickSight可视化预测结果打下基础。