This instructor-led hands-on lab will guide you through the data-centric approach for machine learning, along with the benefits of acquiring relevant data, evaluating and using this data to build ML models.

You’ll learn how to:

• Leverage existing Snowflake data and enrich it with the Snowflake Data Marketplace
• Use Snowflake’s Zero Copy Cloning to maintain ML Training Data Sets Use SageMaker Data Wrangler with Snowflake as a data source
• Perform GUI-based feature engineering
• Analyse data sets for bias that can impact ML models
• Perform quick analysis of features (data sets) for impact and relevancy on ML Models
• Initiate steps for deploying the ML pipeline and integrating ML inference with Snowflake

Lab Prerequisites:

• Snowflake Enterprise Account on AWS with ACCOUNTADMIN access – Snowflake Trial Account will work
• AWS Account with admin access – (AWS Credits will be provided)
• In the AWS account create a VPC and subnets in the region similar to the Snowflake account