spotlight
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maciejkula
Deep recommender models using PyTorch.
There is a small typo in tests/factorization/test_explicit.py. Should read `incompatible` rather than `imcompatible`. Semi-automated pull request generated by https://github.com/timgates42/meticulous/blob/master/docs/NOTE.md
I need to migrate a code that is using spotlight to Azure Machine Learning. When calling the module I am constantly getting these type of errors. My python version is...
I am trying to predict the implicit sequential model. ``` data=[['useID','docid','timestamp']] from sklearn import preprocessing le_usr = preprocessing.LabelEncoder() # user encoder le_itm = preprocessing.LabelEncoder() # item encoder # shift item_ids...
unable to install the library, seems also that its no longer maintained...
Has anyone done something like the metadata embeddings used in LightFM and make it work? I understand in a very high level way how they are created in LightFM. How...
After training the model, I add a new user or item to the Interactions dataset and then try to train the model, but I get the following error:` ValueError: Maximum...
 Here it's mentioned that it's located in the experiments folder in the repo, but I couldn't find it anywhere. I'm keen on experimenting with some improvements on the LSTM...
Hello! Thank you for your great work! In your realisation of bpr loss you use the following formula: ` loss = (1.0 - torch.sigmoid(positive_predictions - negative_predictions)) `. In the original...
My question is I'm thinking is there any reason we can simplify cross entropy loss into the below way instead of what [1] used in cross-entropy. ``` def pointwise_loss(positive_predictions, negative_predictions,...
