Getting Started with Movielens
The MovieLens25M is a popular dataset for recommender systems and is used in academic publications. Most users are familiar with the dataset and the example notebooks teach the basic concepts of NVTabular:
- Learning NVTabular for using GPU-accelerated ETL (Preprocess and Feature Engineering). 
- Getting familiar with NVTabular’s high-level API. 
- Using single-hot/multi-hot categorical input features with NVTabular. 
- Using NVTabular dataloader with TensorFlow Keras model. 
- Using NVTabular dataloader with PyTorch. 
Refer to the following notebooks:
- Training a model: HugeCTR | TensorFlow | PyTorch 
- Serving with Triton Inference Server: HugeCTR | TensorFlow