.. _examples:

Usage Examples
==============

We provide extensive tutorials in Jupyter notebooks under the :repo:`notebooks </tree/main/notebooks>` folder for guidelines on building recommenders, performing model selection, and evaluating performance:

- :repo:`Data Overview </tree/main/notebooks/1_data_overview.ipynb>` provides an overview of data required to train recommender.
- :repo:`Feature Engineering </tree/main/notebooks/2_feature_engineering.ipynb>` gives an overview of methods to create user and item features from structured, unstructured, and sequential data.
- :repo:`Model Selection </tree/main/notebooks/3_model_selection.ipynb>` shows to do model selection by benchmarking recommenders using cross-validation.
- :repo:`Evaluation </tree/main/notebooks/4_evaluation.ipynb>` benchmarks selected recommenders and baselines on test data with detailed evaluations.
- :repo:`Advanced </tree/main/notebooks/5_advanced.ipynb>` demonstrates some advanced functionality.