Snowflake、SageMaker Canvas 与 QuickSight 构建无代码机器学习工作流(三)

Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 3: Visualizing insights with Amazon Quick Sight

精选理由

AWS 教你用 Snowflake、SageMaker Canvas 和 QuickSight 做无代码机器学习,第三部分讲怎么把预测结果做成仪表盘和报告,还能用自然语言提问,比 Excel 强多了。

AI 摘要

本教程是系列第三部分,讲解如何将 Amazon SageMaker Canvas 的欺诈检测预测结果导入 Amazon QuickSight。用户可以在 QuickSight 中构建交互式仪表盘,利用生成式 BI 功能以自然语言回答问题,并为利益相关者发布 AI 生成的执行摘要。

图片来源 · AWS Machine Learning Blog
原文 · AWS Machine Learning Blog

Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 3: Visualizing insights with Amazon Quick Sight

In Part 3 of this no-code ML series, you bring fraud detection predictions to life. Import your Amazon SageMaker Canvas predictions into Amazon Quick Sight, build interactive dashboards, use generative BI to answer questions in natural language, and publish AI-generated executive summaries for stakeholders.

Snowflake、SageMaker Canvas 与 QuickSight 构建无代码机器学习工作流(三) · AI 热点