prediction-flow:由PyTorch实施的基于深度学习的点击率模型
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2021-05-06
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prediction-flow-master.zip （80个子文件） 
prediction-flow-master 
MANIFEST.in 131B .github ISSUE_TEMPLATE bug_report.md 553B feature_request.md 621B
requirements.txt 76B examples amazon amazon-lightning.ipynb 24KB
simple_benchmark.png 13KB prepare_neg.ipynb 14KB amazon.ipynb 66KB movielens movielens-1m.ipynb 88KB ml-1m preprocess.ipynb 40KB train.csv 828KB test.csv 207KB README 5KB CONTRIBUTING.md 5B .travis.yml 56B LICENSE 1KB setup.cfg 39B prediction_flow utils __init__.py 0B metrics __init__.py 0B transformers column log_transformer.py 986B base.py 2KB sequence_encoder.py 4KB __init__.py 378B standard_scaler.py 1KB tests test_sequence_encoder.py 826B test_column_flow.py 744B test_standard_scaler.py 399B test_category_encoder.py 952B __init__.py 0B test_log_transformer.py 326B category_encoder.py 2KB column_flow.py 2KB __init__.py 0B __init__.py 22B features base.py 1KB category_feature.py 2KB __init__.py 221B number_feature.py 590B sequence_feature.py 2KB tests __init__.py 0B test_features.py 3KB features.py 2KB pytorch functions.py 6KB din.py 1KB base.py 2KB interest_net.py 8KB utils.py 980B dnn.py 3KB __init__.py 266B nn interest.py 9KB fm.py 567B __init__.py 403B rnn.py 5KB mlp.py 2KB pooling.py 887B tests test_attention.py 2KB test_pooling.py 787B test_rnn.py 2KB test_interest.py 4KB __init__.py 0B test_fm.py 421B test_mlp.py 564B attention.py 2KB dien.py 4KB data dataset.py 2KB __init__.py 59B tests __init__.py 0B test_dataset.py 3KB tests test_dnn.py 6KB test_deepfm.py 4KB utils.py 2KB __init__.py 0B test_dien.py 6KB test_din.py 2KB test_wide_deep.py 5KB deepfm.py 5KB wide_deep.py 6KB setup.py 2KB README.md 4KB .gitignore 1KB资源评论
