machine-learning-project-walkthrough:在真实数据集上使用Python实现完整的机器学习解决方...
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2021-05-18
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machine-learning-project-walkthrough-master.zip （70个子文件） 
machine-learning-project-walkthrough-master .ipynb_checkpoints 
Machine Learning Project Part 1-checkpoint.ipynb 1.21MB Machine Learning Project Part 2-checkpoint.ipynb 362KB Machine Learning Project Part 3-checkpoint.ipynb 3.59MB Exploratory_Work-checkpoint.ipynb 1.39MB
2016_nyc_benchmarking_data_disclosure_definitions.pdf 99KB images 
correlation_examples.png 15KB local_explanation_one.png 92KB
cover_auto_ml.jpg 221KB tree_verysmall.dot 885B positive_correlations.PNG 7KB df_info.PNG 41KB model_comparison.png 26KB tree_small.png 151KB cover_two.jpg 255KB tree_single_small.dot 2KB density_type.png 95KB tree_verysmall.png 40KB test_prediction_density.png 55KB missing_values.PNG 23KB test_values.png 55KB tpot-ml-pipeline.png 218KB kfold_cv.png 81KB tree_small.dot 3KB tree.png 337KB wrong_explanation_plot.png 99KB score_distribution.png 24KB weather_norm_eui.png 31KB cover_one.jpg 260KB tpot_training_information.PNG 82KB tree_single.png 965KB formatted_train_data.PNG 41KB tree_single_small.png 87KB density_boroughs.png 108KB data_formatted_with_score.PNG 23KB score_vs_eui.png 333KB negative_correlations.PNG 9KB feature_pairs.png 145KB intrepretability_vs_accuracy.png 50KB feature_importances.PNG 17KB feature_importances_graph.png 84KB cover_three.jpg 703KB nestimator_performance.png 38KB tree.dot 5KB individual_node.png 7KB raw_data.PNG 20KB tree_single.dot 13KB lime_wrong_explanation.PNG 31KB annotated_individual_node.PNG 85KB residual_distribution.png 23KB Machine Learning Project Part 1.ipynb 1.18MB Machine Learning Project Part 3.ipynb 3.59MB deprecated Building Data Report.ipynb 1.3MB Exploratory_Work.ipynb 1.39MB
hw_assignment.docx 14KB auto_ml tpot_exported_pipeline.py 1KB README.md 256B Building Data Report.pdf 770KB hw_assignment.pdf 12KB data testing_labels.csv 14KB Y_train.csv 32KB training_features.csv 1.29MB testing_features.csv 569KB no_score.csv 372KB Energy_and_Water_Data_Disclosure_for_Local_Law_84_2017__Data_for_Calendar_Year_2016_.csv 7.9MB X_train.csv 1.83MB cleaned_data.csv 6.4MB X_test.csv 803KB training_labels.csv 32KB Y_test.csv 14KB Machine Learning Project Part 2.ipynb 362KB
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