Getting Started: Session-based Recommendation with Synthetic Data

This example notebook focuses on the following basic concepts of Transformers4Rec:

  • Generating synthetic data of user interactions.

  • Preprocessing sequential data with NVTabular on GPU.

  • Using the NVTabular dataloader with PyTorch.

  • Training a session-based recommendation model with a Transformer architecture (XLNET).

Refer to the following notebooks: