Once data scientists have found the features needed for their model, they can create training data to train their models with. There are a number of things you might do with your features before including them in your training data: do you want to filter out some data (e.g., only users older than 18 years old), do you want to attach online transformation functions (e.g., normalize a numerical feature) to features, how do you want to receive your training data - a Pandas DataFrame or files in CSV or TFRecord or Petastorm file formats. During this 60 minutes workshop, we will walk through how to create and work with training data.
This session requires that you have created some feature groups in your Hopsworks Feature Store. It is enough to run the feature store demo project. If you haven’t done so, here is a video to catch you up before attending this live session.
What you will learn:
Account created on Hopsworks.ai or have access to a Hopsworks cluster.
Hopsworks Feature Store is available both on AWS and Azure as a managed platform.
You can register for free, without having to enter payment details.