spotlight
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maciejkula
Deep recommender models using PyTorch.
I'm playing with implicit models using default `BilinearNet` as representation. Given interactions `test` and some model `model`, one would expect ```python model.predict(test.user_ids) ``` will work, but it raises ```python RuntimeError:...
Is anyone interested in having the same feature set available in TF? I'm considering implementing at least implicit matrix factorization in TF, want to know if it's worth making PRs...
Spotlight already depends on scikit learn (sklearn), so we could delegate even more stuff to the later.
It could be useful to implement diversification metrics like Coverage, Novelty, Diversity, and Serendipity besides the accuracy metrics.
Hi! Very cool project. There are some potential improvements to sequential model found in [Improved Recurrent Neural Networks for Session-based Recommendations](https://arxiv.org/abs/1606.08117). Randomly dropping items from sequences helps to avoid over-fitting...
Hi, do you think it would be worth trying to transform the current `evaluation` code to compute scores in mini-batches, instead of one user at a time as it is...
From #58 Wanted to add the MAP metric to the evaluation.py script. Same interface as mrr_score. If the training dataset is provided, scores of known interactions are set to very...
Hi I saw the "Add model serialization" is on the Trello to do list. If I can serialize the model, can I just reload the old model and just continue...
At the moment, some operations are inefficient due to excessive allocation of new tensors. We could keep tensors around and re-use them for each minibatch, or use in-place operations to...