Whether you are building a startup or adding to a data-intensive application, taking advantage of a cloud data platform and machine learning (ML) technologies is key to innovating and gaining a competitive advantage. Snowflake and AWS (Amazon SageMaker) are bringing you a series of DevDay events to show how to build data-intensive applications with ML.
The success of your machine learning models and applications depends on both the data you have available and how you present the data from training to deployment. This is why data scientists can spend the majority of their time collecting data and transforming it into features. Learn from our instructors how Snowflake and Amazon SageMaker Data Wrangler can help you accelerate the data improvement steps and easily get you from training to production.
In this lab, you’ll have the opportunity to:
- Prepare data and create temporary database clone in Snowflake
- Leverage pre-built feature engineering transformations in SageMaker Data Wrangler
- Train a machine learning model using Amazon SageMaker
- Push model into production that writes inference results in Snowflake
Our Snowflake and AWS instructors will help you follow along and answer your questions live during this lab.