myProjects:有关项目或我对数据进行处理的存储库
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2021-05-08
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myProjects:有关项目或我对数据进行处理的存储库 （140个子文件） 
submission909.csv 4.44MB submissionAugm.csv 4.44MB submission920.csv 4.41MB submissionFastAugm.csv 4.4MB submission.csv 4.4MB synthetic_samples_indexes.csv 629KB synthetic_samples_indexes.csv 629KB .gitignore 1KB
molecules-eda.html 11.57MB Data Exploration.html 2.04MB aptos2019-image-super-resolution.html 1.85MB instant-gratification-eda-and-prediction.html 1.78MB efficientnetb3-multilabel-model-3.html 1.64MB aptos19-densenet-trained-with-old-and-new-data.html 1.54MB aptos19-efficientnet-keras-regression-lb-0-75.html 1.5MB efficientnetb3-regression-model-2.html 1.46MB efficientnetb3-regression-model-1.html 1.15MB lgbm_best_grazder.html 574KB IEEE_2019_XGBoost_Adversarial.html 554KB blending-kernel-top3-model-2-public.html 482KB IEEE_2019_XGBoost_focal_all_feat.html 477KB bert-training.html 473KB catboost_best_grazder.html 470KB lgbm-predicting-molecular-properties.html 416KB gbms-cpu-vs-gpu-400-features-augmentation.html 411KB bert-lstm-rank-blender.html 389KB PredictiveAnalysis_ModelTuning.html 369KB schnet-predicting-molecular-properties-upgrade.html 367KB instant-gratification-ensemble.html 356KB Categorical_Features_CV_Encoding.html 348KB PredictiveAnalysis_ModelTuning_GPU.html 340KB Python_OOP.html 338KB chemistry-of-best-models-upgrade-bronze.html 331KB keras-rnn-training.html 309KB Python_Decorators.html 302KB aptos19-densenet-inference-old-new-data.html 297KB aptos19-inference-efficientnet-keras-regression.html 294KB The Self variable.html 280KB args and kwargs.html 278KB Knock_Knock_tutorial.html 274KB default.html 2KB google_analytics.html 420B ARMA_Subscriber_BikeSharing.inp 1KB ARMA_Customer_BikeSharing.inp 1KB molecules-eda.ipynb 20.34MB Data Exploration.ipynb 1.76MB aptos2019-image-super-resolution.ipynb 1.58MB instant-gratification-eda-and-prediction.ipynb 1.51MB efficientnetb3-multilabel-model-3.ipynb 1.34MB aptos19-densenet-trained-with-old-and-new-data.ipynb 1.25MB aptos19-efficientnet-keras-regression-lb-0-75.ipynb 1.2MB efficientnetb3-regression-model-2.ipynb 1.13MB efficientnetb3-regression-model-1.ipynb 844KB IEEE_2019_XGBoost_Adversarial.ipynb 403KB IEEE_2019_XGBoost_focal_all_feat.ipynb 381KB bert-training.ipynb 161KB lgbm_best_grazder.ipynb 141KB gbms-cpu-vs-gpu-400-features-augmentation.ipynb 91KB Categorical_Features_CV_Encoding.ipynb 86KB catboost_best_grazder.ipynb 86KB blending-kernel-top3-model-2-public.ipynb 69KB chemistry-of-best-models-upgrade-bronze.ipynb 61KB schnet-predicting-molecular-properties-upgrade.ipynb 50KB lgbm-predicting-molecular-properties.ipynb 48KB PredictiveAnalysis_ModelTuning.ipynb 48KB PredictiveAnalysis_ModelTuning_GPU.ipynb 47KB bert-lstm-rank-blender.ipynb 45KB instant-gratification-ensemble.ipynb 35KB keras-rnn-training.ipynb 17KB aptos19-densenet-inference-old-new-data.ipynb 16KB aptos19-inference-efficientnet-keras-regression.ipynb 9KB The Self variable.ipynb 6KB args and kwargs.ipynb 5KB Knock_Knock_tutorial.ipynb 5KB Ford_GoBike.jpeg 206KB aprilgraph.jpeg 94KB aprilgraph2.jpeg 88KB aprilgraph3.jpeg 88KB aprilgraph4.jpeg 87KB aprilgraph5.jpeg 82KB
margaret-weir-GZyjbLNOaFg-unsplash.jpg 2.66MB Hands-on Hadoop.jpg 1.14MB Tableau 10 Advanced Training.jpg 1.13MB R Programming Advanced Analytics.jpg 1.13MB Spark and Python for Big Data.jpg 1.11MB ales-nesetril-734016-unsplash.jpg 181KB mybotchat.jpg 67KB botfatherchat.jpg 56KB botsearch.jpg 16KB LICENSE 11KB ReadMe.md 12KB ReadMe.md 4KB ReadMe.md 4KB ReadMe.md 4KB ReadMe.md 4KB ReadMe.md 3KB ReadMe.md 2KB README.md 2KB ReadMe.md 2KB ReadMe.md 1KB共 140 条
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