Deep learning based recommender systems
Beta
This feature is in Beta.
This page provides notebook examples for building recommendation systems using Serverless GPU compute. These examples demonstrate how to create efficient recommendation models using modern deep learning approaches.
Before running these notebooks, see the Best practices checklist.
Two-tower recommendation model
These notebooks demonstrate how to convert your recommendation data into Mosaic Data Shard (MDS) format and then use that data to create a two-tower recommendation model. This approach is particularly effective for large-scale recommendation systems.
Data preparation: Convert recommendation model dataset to MDS format
First, convert your recommendation dataset to the MDS format for efficient data loading:
Notebook
Model training: Two-tower recommendation model
Train the two-tower recommendation model using the prepared dataset: