Getting Started with Merlin and the MovieLens Dataset#

The MovieLens25M is a popular dataset for recommender systems and is used in academic publications. Most users are familiar with the dataset and we will teach the basic concepts of Merlin:

  • Learn to use NVTabular for using GPU-accelerated feature engineering and data preprocessing.

  • Become familiar with the high-level API for NVTabular.

  • Use single-hot/multi-hot categorical input features with NVTabular.

  • Train a Merlin Model with Tensorflow.

  • Use the Merlin Dataloader with PyTorch.

  • Train a HugeCTR model.

  • Serve recommendations from the Tensorflow model with the Triton Inference Server.

  • Serve recommendations from the HugeCTR model with the Triton Inference Server.

Explore the following notebooks: