toc.yaml

root: index
subtrees:
  - caption: Contents
    entries:
      - file: README.md
        title: Introduction
      - file: examples/tutorials/index.md
        title: Tutorials
        entries:    
            - file: examples/tutorials/basic/index.md
              title: Basic
            - file: examples/tutorials/tf/index.md
              title: TensorFlow
              entries: 
                - file: examples/tutorials/tf/DLRM-Ranking-Model.ipynb
                  title: DLRM Ranking Model
#                 - file: examples/tutorials/tf/TwoTower-Retrieval-Model.ipynb
#                   title: TwoTower Retrieval Model
            - file: examples/tutorials/pytorch/index.md
              title: PyTorch
      - file: guide/recommender_system_guide.rst
        title: Recommender System Guide
      - file: examples/index
        title: Example Notebooks
        subtrees:
          - titlesonly: True
            entries:
              - file: examples/getting-started-movielens/index
                title: Getting Started using the MovieLens Dataset
                entries:
                  - file: examples/getting-started-movielens/01-Download-Convert.ipynb
                    title: MovieLens Download and Convert
                  - file: examples/getting-started-movielens/02-ETL-with-NVTabular.ipynb
                    title: Feature Engineering with NVTabular
                  - file: examples/getting-started-movielens/03-Training-with-HugeCTR.ipynb
                    title: Training with HugeCTR
                  - file: examples/getting-started-movielens/03-Training-with-TF.ipynb
                    title: Training with TensorFlow
                  - file: examples/getting-started-movielens/03-Training-with-PyTorch.ipynb
                    title: Training with PyTorch
                  - file: examples/getting-started-movielens/04-Triton-Inference-with-HugeCTR.ipynb
                    title: Serving the HugeCTR Model with Triton
                  - file: examples/getting-started-movielens/04-Triton-Inference-with-TF.ipynb
                    title: Serving the TensorFlow Model with Triton
              - file: examples/Building-and-deploying-multi-stage-RecSys/index.md
                entries:
                  - file: examples/Building-and-deploying-multi-stage-RecSys/01-Building-Recommender-Systems-with-Merlin.ipynb
                    title: Building the Recommender System
                  - file: examples/Building-and-deploying-multi-stage-RecSys/02-Deploying-multi-stage-RecSys-with-Merlin-Systems.ipynb
                    title: Deploying the Recommender System with Triton
              - file: examples/sagemaker-tensorflow/index.md
                title: Merlin and AWS SageMaker
                entries:
                  - file: examples/sagemaker-tensorflow/sagemaker-merlin-tensorflow.ipynb
              - file: examples/scaling-criteo/index.md
                entries:
                  - file: examples/scaling-criteo/01-Download-Convert.ipynb
                    title: Criteo Download and Convert
                  - file: examples/scaling-criteo/02-ETL-with-NVTabular.ipynb
                    title: Feature Engineering with NVTabular
                  - file: examples/scaling-criteo/03-Training-with-HugeCTR.ipynb
                    title: Training with HugeCTR
                  - file: examples/scaling-criteo/03-Training-with-Merlin-Models-TensorFlow.ipynb
                    title: Training with Merlin Models and TensorFlow
                  - file: examples/scaling-criteo/04-Triton-Inference-with-HugeCTR.ipynb
                    title: Deploy the HugeCTR Model with Triton
                  - file: examples/scaling-criteo/04-Triton-Inference-with-Merlin-Models-TensorFlow.ipynb
                    title: Deploy the TensorFlow Model with Triton
      - file: containers.rst
      - file: support_matrix/index.rst