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Built on PyTorch, RecLib makes it easy to design and evaluate new deep
learning models for recommender system, along with the infrastructure to
easily run them in the cloud or on your laptop. RecLib was designed with the
following principles:
Hyper-modular and lightweight. Use the parts which you like seamlessly with PyTorch.
Extensively tested and easy to extend. Test coverage is above 90% and the example
models provide a template for contributions.
Take object oriented design seriously, making it easy to implement correct
models without the pain.
Experiment friendly. Run reproducible experiments with as little as work possible.
RecLib includes reference implementations of high quality models for CTR, ad ranking and more (see https://github.com/tingkai-zhang/reclib#models).
RecLib is built and maintained by the Tingkai Zhang. The RecLib project is uniquely positioned to provide
state of the art models with high quality engineering.
reclib.common package
Subpackages
reclib.common.testing package
Submodules
reclib.common.testing.test_case module
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reclib.common.checks module
reclib.common.from_params module
reclib.common.params module
reclib.common.registrable module
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reclib.data package
Subpackages
reclib.data.dataset_readers package
Submodules
reclib.data.dataset_readers.azazu module
reclib.data.dataset_readers.criteo module
reclib.data.dataset_readers.movielens module
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reclib.models package
Submodules
reclib.models.afi module
reclib.models.afm module
reclib.models.dcn module
reclib.models.dfm module
reclib.models.ffm module
reclib.models.fm module
reclib.models.fnfm module
reclib.models.fnn module
reclib.models.lr module
reclib.models.model module
reclib.models.nfm module
reclib.models.pnn module
reclib.models.wd module
reclib.models.xdeepfm module
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reclib.modules package
Subpackages
reclib.modules.embedders package
Submodules
reclib.modules.embedders.embedder module
reclib.modules.embedders.embedding module
reclib.modules.embedders.linearembedder module
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reclib.modules.feedforward module
reclib.modules.layers module
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reclib.nn package
Submodules
reclib.nn.activations module
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