├── .gitignore ├── 1-gentle-introductory-series ├── _notebook-related-files │ ├── AOS_Array.png │ ├── AOS_CSV.png │ ├── AOS_DataLayout.png │ ├── AOS_Pandas.png │ ├── CSR_Array.png │ ├── CSR_Matrix.png │ ├── CSR_Pandas.png │ ├── Capture.png │ ├── DataFlow.png │ ├── DistributedWF.png │ ├── ExampleIncomingData.png │ ├── HeterogenTable_1.png │ ├── HeterogenTable_2.png │ ├── HomogenArray.png │ ├── HomogenCSV.png │ ├── HomogenPandas.png │ ├── HomogenTable_1.png │ ├── Image2.png │ ├── Image3.png │ ├── ModelPortRibbon.png │ ├── QualityMetRibbon.png │ ├── SOA_Array.png │ ├── SOA_CSV.png │ ├── SOA_DataLayout.png │ ├── SOA_Pandas.png │ ├── SampleBatchFile.csv │ ├── SampleSOABatchFile.csv │ ├── SymTri_Array.png │ ├── SymTri_Pandas.png │ ├── SymmetricTriangular.png │ ├── TrainPredictRibbon.png │ ├── TrainPredictWF.png │ ├── TrainPredictWFImage.png │ ├── normalization.csv │ └── testSVM.py ├── volume-1-data-structures.ipynb ├── volume-2-basic-operations-on-numeric-tables.ipynb └── volume-3-analytics-model-building-deployment.ipynb ├── 2-pre-built-helper-classes ├── DecisionForest │ ├── DF-class-documentation.docx │ ├── DF-classification-usage-example.py │ ├── DF-regression-usage-example.py │ └── DecisionForest.py ├── GridSearch │ ├── GridSearch.py │ ├── README.md │ └── usage-examples │ │ ├── 1-testNaiveBayes.py │ │ ├── 2-1-testAdaBoost.py │ │ ├── 2-2-testBrownBoost.py │ │ ├── 2-3-testLogBoost.py │ │ ├── 3-1-testSVM.py │ │ ├── 5-testKNN.py │ │ ├── 6-testDecisionTree.py │ │ ├── 7-testDecisionForest.py │ │ └── 8-testGbt.py ├── Kmeans │ ├── Kmeans.py │ ├── kmeans-class-documentation.docx │ └── kmeans-usage-example.py ├── LinearRegression │ ├── LinearRegression.py │ ├── linear-regression-class-documentation.docx │ ├── linear-regression-class-usage-example.py │ └── reg_quality_metrics.py ├── PCA │ ├── PCA-class-documentation.docx │ ├── PCA.py │ └── pca-class-usage-example.py ├── README.md ├── RidgeRegression │ ├── RidgeRegression.py │ ├── ridge-regression-class-documentation.docx │ └── ridge-regression-class-usage-example.py └── SVM │ ├── SVM-class-documentation.docx │ ├── SVM.py │ ├── svm-class-binary-usage-example.py │ └── svm-class-multi-usage-example.py ├── 3-custom-modules └── customUtils │ └── __init__.py ├── 4-interactive-tutorials ├── LR_example.ipynb ├── NaiveBayes_online_example.ipynb ├── NumericTables_example.ipynb ├── Regression_online_example.ipynb ├── SVM_example.ipynb ├── Tutorial-solutions │ ├── LR_example.py │ ├── NaiveBayes.py │ ├── SVM.py │ └── kmeansORpca.py ├── kmeans_example.ipynb └── mldata │ ├── 20newsgroups.coo.1.csv │ ├── 20newsgroups.coo.2.csv │ ├── 20newsgroups.coo.3.csv │ ├── 20newsgroups.coo.4.csv │ ├── 20newsgroups.coo.5.csv │ ├── 20newsgroups.labels.1.csv │ ├── 20newsgroups.labels.2.csv │ ├── 20newsgroups.labels.3.csv │ ├── 20newsgroups.labels.4.csv │ ├── 20newsgroups.labels.5.csv │ ├── housing.data │ ├── housing.data.test.csv │ ├── housing.data.train.csv │ ├── movement_libras.data │ ├── 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