[{"title":"( 48 个子文件 35.67MB ) 预测沃尔玛天蓝色销售额","children":[{"title":"Forecasting-Walmart-sales-with-Azure-master","children":[{"title":"images","children":[{"title":"model_deployed_autoML_studio_02.JPG <span style='color:#111;'> 65.28KB </span>","children":null,"spread":false},{"title":"time_series_split.JPG <span style='color:#111;'> 34.15KB </span>","children":null,"spread":false},{"title":"automl_widget_01.JPG <span style='color:#111;'> 92.74KB </span>","children":null,"spread":false},{"title":"microsoft-azure-640x401.png <span style='color:#111;'> 12.63KB </span>","children":null,"spread":false},{"title":"automl_log_deployed_model.JPG <span style='color:#111;'> 297.72KB </span>","children":null,"spread":false},{"title":"hd_best_model_0902_notebook.JPG <span style='color:#111;'> 71.74KB </span>","children":null,"spread":false},{"title":"architecture_diagram.JPG <span style='color:#111;'> 38.25KB </span>","children":null,"spread":false},{"title":"automl_deployment_status.JPG <span style='color:#111;'> 42.91KB </span>","children":null,"spread":false},{"title":"hd_widget_0902_05_log_metrics.JPG <span style='color:#111;'> 163.11KB </span>","children":null,"spread":false},{"title":"hd_best_model_0902_details_02.JPG <span style='color:#111;'> 60.63KB </span>","children":null,"spread":false},{"title":"model_deployed_autoML_studio_01.JPG <span style='color:#111;'> 56.81KB </span>","children":null,"spread":false},{"title":"hd_widget_0902_04.JPG <span style='color:#111;'> 80.08KB </span>","children":null,"spread":false},{"title":"best_model_details_01.JPG <span style='color:#111;'> 71.58KB </span>","children":null,"spread":false},{"title":"hd_best_model_0902_details_01.JPG <span style='color:#111;'> 62.38KB </span>","children":null,"spread":false},{"title":"best_model_details_02.JPG <span style='color:#111;'> 66.87KB </span>","children":null,"spread":false},{"title":"Walmart1_Logo-scaled.jpg <span style='color:#111;'> 136.78KB </span>","children":null,"spread":false},{"title":"hd_top_10_0902.JPG <span style='color:#111;'> 117.59KB </span>","children":null,"spread":false},{"title":"obtain_score.JPG <span style='color:#111;'> 26.68KB </span>","children":null,"spread":false},{"title":"project_workflow.JPG <span style='color:#111;'> 47.58KB </span>","children":null,"spread":false},{"title":"models_automl.JPG <span style='color:#111;'> 95.30KB </span>","children":null,"spread":false},{"title":"automl_best_model_notebook.JPG <span style='color:#111;'> 91.17KB </span>","children":null,"spread":false},{"title":"hd_widget_0902_02.JPG <span style='color:#111;'> 69.07KB </span>","children":null,"spread":false},{"title":"hd_widget_0902_03.JPG <span style='color:#111;'> 36.70KB </span>","children":null,"spread":false},{"title":"hd_widget_0902_01.JPG <span style='color:#111;'> 108.83KB </span>","children":null,"spread":false},{"title":"automl_widget_02.JPG <span style='color:#111;'> 41.66KB </span>","children":null,"spread":false}],"spread":false},{"title":"automl-final-version-090221.ipynb <span style='color:#111;'> 378.51KB </span>","children":null,"spread":false},{"title":"automl_best_model.zip <span style='color:#111;'> 2.17MB </span>","children":null,"spread":false},{"title":"hyperparameter-tuning-final-version-090221.ipynb <span style='color:#111;'> 101.08KB </span>","children":null,"spread":false},{"title":"myenv.yml <span style='color:#111;'> 749B </span>","children":null,"spread":false},{"title":"data","children":[{"title":"walmart_tx_stores_10_items_with_day.csv <span style='color:#111;'> 5.98MB </span>","children":null,"spread":false}],"spread":true},{"title":"automl.log <span style='color:#111;'> 5.29KB </span>","children":null,"spread":false},{"title":"train.py <span style='color:#111;'> 11.15KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"train.cpython-36.pyc <span style='color:#111;'> 10.27KB </span>","children":null,"spread":false}],"spread":true},{"title":"temp","children":[{"title":"automl-final-version-090221.ipynb <span style='color:#111;'> 378.40KB </span>","children":null,"spread":false},{"title":"automl-final-version-090221 (1).ipynb <span style='color:#111;'> 378.40KB </span>","children":null,"spread":false},{"title":".ipynb_checkpoints","children":[{"title":"hyperparameter-tuning-final-version-080221-checkpoint.ipynb <span style='color:#111;'> 140.18KB </span>","children":null,"spread":false},{"title":"hyperparameter-tuning-final-version-070221-checkpoint.ipynb <span style='color:#111;'> 139.68KB </span>","children":null,"spread":false},{"title":"automl-final-version-070221-checkpoint.ipynb <span style='color:#111;'> 377.06KB </span>","children":null,"spread":false},{"title":"hyperparameter-tuning-final-version-070221-TO_RERUN-checkpoint.ipynb <span style='color:#111;'> 139.68KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"automl_walmart_forecasting_errors.log <span style='color:#111;'> 117B </span>","children":null,"spread":false},{"title":"bst-model.pkl <span style='color:#111;'> 398.84KB </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 342B </span>","children":null,"spread":false},{"title":"azureml_automl.log <span style='color:#111;'> 3.57KB </span>","children":null,"spread":false},{"title":"video","children":[{"title":"udacity_capstone_DaniellePaesBarretto.mp4 <span style='color:#111;'> 35.08MB </span>","children":null,"spread":false}],"spread":false},{"title":"01-create_sample_data_walmart.ipynb <span style='color:#111;'> 156.92KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 16.65KB </span>","children":null,"spread":false},{"title":"score_forecast.py <span style='color:#111;'> 2.97KB </span>","children":null,"spread":false},{"title":"config.json <span style='color:#111;'> 161B </span>","children":null,"spread":false}],"spread":false}],"spread":true}]