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AWS enables no-code ML workflow with Snowflake, SageMaker Canvas, and Quick Sight

By PulseAugur Editorial · [5 sources] ·

This three-part series details how to build a no-code machine learning workflow using AWS services. Part 1 focuses on setting up the necessary Snowflake and AWS environments. Part 2 guides users through data preparation and model building with Amazon SageMaker Canvas, utilizing tools like Data Wrangler and the XGBoost algorithm for fraud detection. The final part explains how to visualize these ML predictions using Amazon Quick Sight, integrating them into interactive dashboards for business intelligence. AI

IMPACT Democratizes machine learning by enabling business users to build predictive models without coding expertise.

RANK_REASON Blog series detailing the integration of multiple AWS services for a specific use case.

Read on AWS Machine Learning Blog →

AI-generated summary · Google Gemini · from 5 sources. How we write summaries →

AWS enables no-code ML workflow with Snowflake, SageMaker Canvas, and Quick Sight

COVERAGE [5]

  1. AWS Machine Learning Blog TIER_1 English(EN) · Anu Kaggadasapura Nagaraja ·

    Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 1: Setting up your Snowflake environment

    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, layin…

  2. AWS Machine Learning Blog TIER_1 English(EN) · Anu Kaggadasapura Nagaraja ·

    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

    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 int…

  3. AWS Machine Learning Blog TIER_1 English(EN) · Anu Kaggadasapura Nagaraja ·

    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…

  4. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    🤖 Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 1: Setting up your Snowflake environment Healthcare, retail, and l

    🤖 Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 1: Setting up your Snowflake environment Healthcare, retail, and life sciences teams store large volumes of operational data in Snowflake, but turning it into predictions is hard. In Par…

    LINKS aws.amazon.com/…/build-a-no-code-ml-workf…
  5. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

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

    🤖 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 In Part 2 of this no-code ML series, you connect Amazon SageMaker Canvas to Snowflake, prepare and join transaction da…

    LINKS aws.amazon.com/…/build-a-no-code-ml-workf…

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