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: