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  2. Search — LightFM 1.16 documentation

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  3. lightfm.data.rst.txt

    Dataset construction ========== .. automodule:: lightfm.data :members: :undoc-members: :show-inheritance:
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  4. index.rst.txt

    .. include:: home.rst Contents ======== .. toctree:: :maxdepth: 2 Home <home> Quickstart <quickstart> The LightFM model class <lightfm> Model evaluation <lightfm.evaluation> Cross validation <cross...
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  5. Examples — LightFM 1.16 documentation

    » Examples Examples  Many of the examples can be viewed (and run) as Jupyter notebooks in the examples directory of ...
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  6. examples.rst.txt

    Examples ========== Many of the examples can be viewed (and run) as Jupyter notebooks in the `examples directory <https://github.com/lyst/lightfm/tree/master/examples>`_ of the LightFM repository. ...
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  7. cross_validation.rst.txt

    Cross-validation ========== .. automodule:: lightfm.cross_validation :members: :undoc-members:
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  8. learning_schedules.rst.txt

    Using different learning schedules ========== ``lightfm`` implements two learning schedules: adagrad and adadelta. Neither is clearly superior, and, like other hyperparameter choices, the best lear...
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  9. movielens_implicit.rst.txt

    An implicit feedback recommender for the Movielens dataset ========== Implicit feedback ---------- For some time, the recommender system literature focused on explicit feedback: the Netflix prize f...
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  10. datasets.rst.txt

    Datasets ========== .. autofunction:: lightfm.datasets.movielens.fetch_movielens .. autofunction:: lightfm.datasets.stackexchange.fetch_stackexchange
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  11. home.rst.txt

    Welcome to LightFM's documentation! ========== LightFM is a Python implementation of a number of popular recommendation algorithms for both implicit and explicit feedback. It also makes it possible...
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