toc:
- heading: "Beginner"
  style: divider
- title: "Recommender basics"
  style: accordion
  section:
  - title: "Recommending movies: retrieval"
    path: /recommenders/examples/basic_retrieval
  - title: "Recommending movies: ranking"
    path: /recommenders/examples/basic_ranking
  - title: "Retrieval with distribution strategy"
    path: /recommenders/examples/diststrat_retrieval
  - title: "Retrieval with sequential model"
    path: /recommenders/examples/sequential_retrieval
  - title: "Ranking with TFX"
    path: /recommenders/examples/ranking_tfx
  - title: "Large Embedding with TPU"
    path: /recommenders/examples/tpu_embedding_layer
- title: "Using rich features"
  style: accordion
  section:
  - title: "Feature preprocessing"
    path: /recommenders/examples/featurization
  - title: "Leveraging context features"
    path: /recommenders/examples/context_features
  - title: "Building deep retrieval models"
    path: /recommenders/examples/deep_recommenders
- heading: "Intermediate"
  style: divider
- title: "Multitask recommenders"
  path: /recommenders/examples/multitask
- title: "Cross networks"
  path: /recommenders/examples/dcn
- title: "Efficient serving"
  path: /recommenders/examples/efficient_serving
- title: "Listwise ranking"
  path: /recommenders/examples/listwise_ranking

toc:
- heading: "Beginner"
  style: divider
- title: "Recommender basics"
  style: accordion
  section:
  - title: "Recommending movies: retrieval"
    path: /recommenders/examples/basic_retrieval
  - title: "Recommending movies: ranking"
    path: /recommenders/examples/basic_ranking
  - title: "Retrieval with distribution strategy"
    path: /recommenders/examples/diststrat_retrieval
  - title: "Retrieval with sequential model"
    path: /recommenders/examples/sequential_retrieval
  - title: "Ranking with TFX"
    path: /recommenders/examples/ranking_tfx
- title: "Using rich features"
  style: accordion
  section:
  - title: "Feature preprocessing"
    path: /recommenders/examples/featurization
  - title: "Leveraging context features"
    path: /recommenders/examples/context_features
  - title: "Building deep retrieval models"
    path: /recommenders/examples/deep_recommenders
- heading: "Intermediate"
  style: divider
- title: "Multitask recommenders"
  path: /recommenders/examples/multitask
- title: "Cross networks"
  path: /recommenders/examples/dcn
- title: "Efficient serving"
  path: /recommenders/examples/efficient_serving
- title: "Listwise ranking"
  path: /recommenders/examples/listwise_ranking

Remove the TPU embedding tutorial url in TFRS.
Remove the TPU embedding tutorial url in TFRS.

PiperOrigin-RevId: 467815764
