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lightfm.data.rst.txt
Dataset construction ========== .. automodule:: lightfm.data :members: :undoc-members: :show-inheritance:making.lyst.com/lightfm/docs/_sources/lightfm.data.rst.txtRegistered: Fri Apr 26 08:00:51 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 129 bytes - Viewed (0) -
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...making.lyst.com/lightfm/docs/_sources/index.rst.txtRegistered: Fri Apr 26 07:58:44 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 433 bytes - Viewed (1) -
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. ...making.lyst.com/lightfm/docs/_sources/examples.rst.txtRegistered: Fri Apr 26 08:01:32 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 537 bytes - Viewed (0) -
cross_validation.rst.txt
Cross-validation ========== .. automodule:: lightfm.cross_validation :members: :undoc-members:making.lyst.com/lightfm/docs/_sources/cross_validation.rst.txtRegistered: Fri Apr 26 08:01:01 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 108 bytes - Viewed (0) -
faq.rst.txt
=== FAQ === Does LightFM have a GPU-based implementation? ========== No, there is no option to run training or inference on the GPU with LightFM. There are currently no plans to change this. See ht...making.lyst.com/lightfm/docs/_sources/faq.rst.txtRegistered: Fri Apr 26 08:00:54 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 2.4K bytes - Viewed (0) -
hybrid_crossvalidated.rst.txt
Item cold-start: recommending StackExchange questions ========== In this example we'll use the StackExchange dataset to explore recommendations under item-cold start. Data dumps from the StackExcha...making.lyst.com/lightfm/docs/_sources/examples/hybrid_crossvalidated.rst.txtRegistered: Fri Apr 26 08:01:51 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 8.4K bytes - Viewed (0) -
lightfm.evaluation.rst.txt
Model evaluation ========== .. automodule:: lightfm.evaluation :members: :undoc-members: :show-inheritance:making.lyst.com/lightfm/docs/_sources/lightfm.evaluation.rst.txtRegistered: Fri Apr 26 08:00:34 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 136 bytes - Viewed (0) -
quickstart.rst.txt
Quickstart ========== In this example, we'll build an implicit feedback recommender using the Movielens 100k dataset (http://grouplens.org/datasets/movielens/100k/). The code behind this example is...making.lyst.com/lightfm/docs/_sources/quickstart.rst.txtRegistered: Fri Apr 26 08:01:28 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 4.9K bytes - Viewed (0) -
dataset.rst.txt
Building datasets ========== In this example, we'll use LightFM's built-in ``Dataset`` class to build an interaction dataset from raw data. The goal is to demonstrate how to go from raw data (lists...making.lyst.com/lightfm/docs/_sources/examples/dataset.rst.txtRegistered: Fri Apr 26 08:01:39 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 6K bytes - Viewed (0) -
warp_loss.rst.txt
Learning-to-rank using the WARP loss ========== LightFM is probably the only recommender package implementing the WARP (Weighted Approximate-Rank Pairwise) loss for implicit feedback learning-to-ra...making.lyst.com/lightfm/docs/_sources/examples/warp_loss.rst.txtRegistered: Fri Apr 26 08:01:42 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 6.9K bytes - Viewed (0)