Machine Learning Mastery With Python
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README
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Welcome to Machine Learning Mastery With Python!
Your download contains:
1. The Ebook:
machine_learning_mastery_with_python.pdf
2. Sample Code:
code/
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Any questions at all, contact me direction via email: jason@MachineLearningMastery.com
Kind Regards,
Jason.
machine_learning_mastery_with_python.zip （94个子文件） 
README.txt 444B
machine_learning_mastery_with_python.pdf 1.81MB
code chapter_10 
pima-indians-diabetes.data.csv 23KB regression_mae.py 702B classification_confusion_matrix.py 729B classification_report.py 729B housing.csv 48KB classification_auc.py 659B classification_logloss.py 668B classification_accuracy.py 666B regression_mse.py 716B regression_rsquared.py 681B chapter_18 project_template.py 599B chapter_06 pima-indians-diabetes.data.csv 23KB boxplot.py 339B density_plots.py 332B correlation_matrix.py 564B correlation_matrix_generic.py 439B histograms.py 272B scatterplot_matrix.py 321B chapter_20 housing.csv 48KB project_regression_boston.py 7KB chapter_19 iris.data.csv 4KB project_classification_iris.py 3KB chapter_17 pima-indians-diabetes.data.csv 23KB save_model_joblib.py 857B save_model_pickel.py 845B chapter_16 pima-indians-diabetes.data.csv 23KB random_search.py 652B grid_search.py 621B chapter_21 project_classification_sonar.py 7KB sonar.all-data.csv 86KB chapter_13 pima-indians-diabetes.data.csv 23KB race_algorithms.py 1KB chapter_11 support_vector_machines_classification.py 525B pima-indians-diabetes.data.csv 23KB logistic_regression.py 595B linear_discriminant_analysis.py 604B classification_and_regression_trees_classification.py 565B k_nearest_neighbors_classification.py 580B gaussian_naive_bayes.py 564B chapter_07 rescale_data.py 582B normalize_data.py 563B pima-indians-diabetes.data.csv 23KB binarization.py 556B standardize_data.py 573B chapter_09 loocv.py 634B pima-indians-diabetes.data.csv 23KB cross_validation.py 670B shuffle_split.py 733B train_test.py 659B chapter_03 python_crash_course.py 1KB pandas_crash_course.py 552B numpy_crash_course.py 621B matplotlib_crash_course.py 407B chapter_14 pima-indians-diabetes.data.csv 23KB standardize_model_pipeline.py 891B feature_union_model_pipeline.py 1KB chapter_08 pima-indians-diabetes.data.csv 23KB recursive_feature_elimination.py 614B univariate_selection.py 715B pca.py 508B feature_importance.py 467B chapter_05 pima-indians-diabetes.data.csv 23KB skew.py 249B describe.py 353B pearson_correlation.py 377B head.py 246B class_distribution.py 277B dimensions.py 250B data_types.py 257B chapter_02 scipy_versions.py 263B sklearn_version.py 72B chapter_15 pima-indians-diabetes.data.csv 23KB voting_ensemble_classification.py 974B bagged_cart_classification.py 750B gradient_boosting_classification.py 670B extra_trees_classification.py 654B adaboost_classification.py 630B random_forest_classification.py 660B chapter_12 elastic_net.py 642B housing.csv 48KB lasso_regression.py 627B k_nearest_neighbors_regression.py 650B support_vector_machines_regression.py 612B ridge_regression.py 627B classification_and_regression_trees_regression.py 659B linear_regression.py 650B chapter_04 pima-indians-diabetes.data.csv 23KB load_csv_np_url.py 211B load_csv_np.py 183B load_csv.py 283B load_csv_pandas_url.py 224B load_csv_pandas.py 268B资源评论
