├── Chapter_ANN ├── CCPP_FFNN.ipynb ├── CCPP_FFNN.py ├── CCPP_FFNN_gridSearch.ipynb ├── CCPP_data_explore.ipynb ├── CCPP_data_explore.py ├── Folds5x2_pp.xlsx ├── ccpp_FFNN_gridSearch.py ├── debutanizer_FFNN.ipynb ├── debutanizer_FFNN.py ├── debutanizer_PLS.ipynb ├── debutanizer_PLS.py ├── debutanizer_data.txt ├── debutanizer_dataExplore.ipynb ├── debutanizer_dataExplore.py ├── info.txt ├── kamyr-digester.csv ├── kamyr_data_FFNN_earlyStopping.ipynb ├── kamyr_data_FFNN_earlyStopping.py ├── quadratic_function_singleLayer.ipynb └── quadratic_function_singleLayer.py ├── Chapter_BestPractices ├── 3Way_Holdout_Method.ipynb ├── 3wayHoldout_Method.py ├── Centering_Scaling.ipynb ├── Centering_Scaling.py ├── Feature_Engineering_OneHotEncoding.ipynb ├── Feature_Engineering_OneHotEncoding.py ├── Feature_Engineering_quadraticFit.ipynb ├── Feature_Engineering_quadraticFit.py ├── GridSearchCV.ipynb ├── GridSearchCV.py ├── Holdout_Method.ipynb ├── Holdout_Method.py ├── Pipeline_quadraticFit.ipynb ├── Pipeline_quadraticFit.py ├── Regularization.ipynb ├── ValidationCurve.ipynb ├── ValidationCurve.py ├── info.txt ├── kFold_CrossValidation.ipynb ├── kFold_CrossValidation.py ├── quadratic_raw_data.csv └── regularization.py ├── Chapter_Clustering_GMM ├── DBSCAN_clustering.ipynb ├── DBSCAN_clustering.py ├── DBSCAN_illustration.ipynb ├── DBSCAN_illustration.py ├── Etch_data_explore.ipynb ├── Etch_data_explore.py ├── GMM_clustering.ipynb ├── GMM_clustering.py ├── GMM_illustration.ipynb ├── GMM_illustration.py ├── MACHINE_Data.mat ├── Metal_etch_complete_data_visualize.ipynb ├── Metal_etch_complete_data_visualize.py ├── ProcessMonitoring_GMM.ipynb ├── ProcessMonitoring_GMM.py ├── k_means_clustering.ipynb ├── k_means_clustering.py ├── k_means_failure.ipynb └── k_means_failure.py ├── Chapter_DecisionTrees_EnsembleLearning ├── Bagging_illustration.ipynb ├── Bagging_illustration.py ├── DT_illustration.ipynb ├── DT_illustration.py ├── RF_illustration.ipynb ├── RF_illustration.py ├── SoftSensing_ConcreteStrength_PLS.ipynb ├── SoftSensing_ConcreteStrength_PLS.py ├── SoftSensing_ConcreteStrength_RF.ipynb ├── SoftSensing_ConcreteStrength_RF.py ├── SoftSensing_WastewaterPlant_PLS.ipynb ├── SoftSensing_WastewaterPlant_PLS.py ├── SoftSensing_WastewaterPlant_XGBoost.ipynb ├── SoftSensing_WastewaterPlant_XGBoost.py ├── cement_strength.txt ├── info.txt ├── water-treatment.data └── water-treatment.names ├── Chapter_LatentVariable1 ├── DimensionalityReduction.ipynb ├── DimensionalityReduction.py ├── DynamicPCA.ipynb ├── DynamicPCA.py ├── KernelPCA.ipynb ├── KernelPCA.py ├── LDPE.csv ├── ProcessMonitoring_PCA.ipynb ├── ProcessMonitoring_PCA.py ├── ProcessMonitoring_PLS.ipynb ├── ProcessMonitoring_PLS.py ├── SoftSensor_PLS.ipynb ├── kamyr-digester.csv ├── proc1a.xls └── softSensor_PLS.py ├── Chapter_LatentVariable2 ├── DimensionalityReduction_FDA.ipynb ├── DimensionalityReduction_FDA.py ├── DimensionalityReduction_ICA.ipynb ├── DimensionalityReduction_ICA.py ├── FDA_illustration.ipynb ├── FDA_illustration.py ├── FaultClassification_FDA.ipynb ├── FaultClassification_FDA.py ├── ICA_illustration.ipynb ├── ICA_illustration.py ├── ProcessMonitoring_ICA.ipynb ├── ProcessMonitoring_ICA.py ├── ProcessMonitoring_PCA.ipynb ├── ProcessMonitoring_PCA.py ├── TEP_data_explore.ipynb ├── TE_processData_explore.py ├── d00.dat ├── d00_te.dat ├── d01.dat ├── d01_te.dat ├── d02.dat ├── d02_te.dat ├── d03.dat ├── d03_te.dat ├── d04.dat ├── d04_te.dat ├── d05.dat ├── d05_te.dat ├── d06.dat ├── d06_te.dat ├── d07.dat ├── d07_te.dat ├── d08.dat ├── d08_te.dat ├── d09.dat ├── d09_te.dat ├── d10.dat ├── d10_te.dat ├── d11.dat ├── d11_te.dat ├── d12.dat ├── d12_te.dat ├── d13.dat ├── d13_te.dat ├── d14.dat ├── d14_te.dat ├── d15.dat ├── d15_te.dat ├── d16.dat ├── d16_te.dat ├── d17.dat ├── d17_te.dat ├── d18.dat ├── d18_te.dat ├── d19.dat ├── d19_te.dat ├── d20.dat ├── d20_te.dat ├── d21.dat ├── d21_te.dat └── info.txt ├── Chapter_OtherUsefulMethods ├── FD-kNN.ipynb ├── FD-kNN.py ├── KDE_ControlLimits_for_ICAmonitoring.ipynb ├── KDE_ControlLimits_for_ICAmonitoring.py ├── KDE_GridSearchCV.ipynb ├── KDE_GridSearchCV.py └── info.txt ├── Chapter_Preprocessing ├── EmbeddedMethods_Lasso.py ├── Embedded_Method_Lasso.ipynb ├── MLR_VSdata.py ├── Missing_data_imputation.ipynb ├── Missing_data_imputation.py ├── MultivariateLinearRegression_VSdata.ipynb ├── Multivariate_Outliers_MCD.ipynb ├── Multivariate_Outliers_MahalanobisDistance.ipynb ├── Multivariate_outliers_MCD.py ├── Multivariate_outliers_Mahalanobis_distance.py ├── Univariate_Outliers.ipynb ├── Univariate_Outliers.py ├── VSdata.csv ├── VSdata_val.csv ├── WrapperMethods_backward_SFS.py ├── Wrapper_Methods_backward_SFS.ipynb ├── complex2D_outlier.csv ├── deNoising_process_signals.py ├── denoising_process_signals.ipynb ├── filterMethods.py ├── filter_Methods.ipynb ├── info.txt ├── noisy_flow_signal.csv └── simple2D_outlier.csv ├── Chapter_RNN ├── AircraftEngine_dataExploration.ipynb ├── AircraftEngine_dataExplore.py ├── PM_test.txt ├── PM_train.txt ├── PM_truth.txt ├── SISO_Heater_system_RNN.ipynb ├── SISO_Heater_system_RNN.py ├── TCLab_test_data.txt ├── TCLab_train_data.txt ├── TEP_dataExploration.ipynb ├── TEP_dataExploration.py ├── TEP_faultClassification_RNN.ipynb ├── TEPclassification_RNN.py ├── info.txt ├── predictiveMaint_Regression_RNN.py ├── predictiveMaint_binaryClassification_RNN.ipynb ├── predictiveMaint_binaryClassification_RNN.py └── predictiveMaint_regression_RNN.ipynb ├── Chapter_ReinforcementLearning ├── RL_agent_train_test.ipynb ├── RL_agent_train_test.py ├── Tank_Environment.py ├── actor_saved │ ├── keras_metadata.pb │ ├── saved_model.pb │ └── variables │ │ ├── variables.data-00000-of-00001 │ │ └── variables.index ├── disturbance_200.csv └── info.txt ├── Chapter_ScriptingEnvironment ├── NumpyBasics.ipynb ├── NumpyBasics.py ├── PandasBasics.ipynb ├── PandasBasics.py ├── PythonBasics.ipynb ├── PythonBasics.py ├── info.txt ├── quadratic_raw_data.csv ├── typicalML_script.ipynb └── typicalML_script.py ├── Chapter_SupportVectorMachines ├── Metal_etch_2DPCA_testData.csv ├── Metal_etch_2DPCA_trainingData.csv ├── SVDD_FaultDetection.ipynb ├── SVDD_FaultDetection.py ├── SVDD_OneClassClassification.ipynb ├── SVDD_OneClassClassification.py ├── SVDD_toyDataset.csv ├── SVM_BinaryClassification.ipynb ├── SVM_BinaryClassification.py ├── SVM_Kernel_BinaryClassification.ipynb ├── SVM_Kernel_BinaryClassification.py ├── SVM_Kernel_BinaryClassification_noGridSearch.py ├── SVM_SoftMarginClassification.ipynb ├── SVM_SoftMarginClassification.py ├── SVR_illustration.ipynb ├── SVR_illustration.py ├── debutanizer_Softsensing_PLS.ipynb ├── debutanizer_Softsensing_PLS.py ├── debutanizer_Softsensing_SVR.ipynb ├── debutanizer_Softsensing_SVR.py ├── debutanizer_data.txt ├── info.txt ├── polymer.dat ├── polymerPlantData_Softsensing_PLS.ipynb ├── polymerPlantData_Softsensing_PLS.py ├── polymerPlantData_Softsensing_SVR.ipynb ├── polymerPlantData_Softsensing_SVR.py ├── toyDataset.csv └── toyDataset2.csv ├── Chapter_WebDeployment ├── FDD.py ├── FDD_withHTML.py ├── FDD_withoutHTML.py ├── PCAmetrics_history.pickle ├── PCAmodelData.pickle ├── ProcessMonitoring_PCA.py ├── contributionPlot.png ├── frontEndTemplate.html ├── helloWorld.py ├── info.txt ├── metricPlot.png ├── proc1a.xlsx ├── processLatestDatabase_local.csv └── sample.html ├── Images ├── Book3_coverPage.JPG └── ML-for-PSE-2023Edition-CoverPage.JPG ├── LICENSE └── README.md /Chapter_ANN/CCPP_FFNN.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ML-PSE/Machine_Learning_for_PSE/HEAD/Chapter_ANN/CCPP_FFNN.ipynb -------------------------------------------------------------------------------- /Chapter_ANN/CCPP_FFNN.py: -------------------------------------------------------------------------------- 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