Launching Hopsworks Clusters in your AWS SageMaker Account
This 2 hours hands-on masterclass provides an introduction to the fundamentals of feature stores as key components in enterprises’ artificial intelligence architectures and how to integrate the Hopsworks Feature Store with AWS SageMaker.
A feature store enables machine learning (ML) features to be registered, discovered, and used as part of ML pipelines, thus making it easier to transform and validate the training data that is fed into machine learning systems. Feature stores can also enable consistent engineering of features between training and inference, but to do so, they need a common data processing platform.
The Hopsworks Feature Store is the world’s first platform for managing and serving features for machine learning available as open-source, Enterprise or as a managed platform on AWS (www.hopsworks.ai).
Join us to learn:
- Learn how the Feature Store enables end-to-end ML pipelines to be factored into feature engineering and data science stages that each can run at different cadences
- How to sign up for a free Hopsworks account
- How to setup a connection between your Hopsworks and AWS SageMaker accounts
- How to create training dataset in s3 from Sagemaker (query planner and hints)
- From an experienced university professor and founder of the world’s first feature store.
This course is a good fit for you if:
- You have or are pursuing a bachelor or master degree in Data Science or Software Engineering;
- You are a user of AWS SageMaker;
- You are interested to learn more about artificial intelligence and machine learning;
- You have lots of questions and are looking for someone to answer them all!
This masterclass is part of Logical Clock’s learning series and will be led by Dr. Jim Dowling, lead architect and CEO of Logical Clocks and Associate Professor at KTH Royal Institute of Technology.
Register now, we look forward to connecting with you soon.