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

Datasets ========== .. autofunction:: lightfm.datasets.movielens.fetch_movielens .. autofunction:: lightfm.datasets.stackexchange.fetch_stackexchange

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...

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...

=== 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...

» Python Module Index Python Module Index l l lightfm lightfm.cross_validation lightfm.data lightfm.evaluation

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...

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...

LightFM ========== .. autoclass:: lightfm.LightFM :members: :undoc-members:

» Overview: module code All modules for which code is available lightfm.cross_validation lightfm.data lightfm.dataset...