Feature Eng: RFECV
Models: LogR, KNN & RandForest
Validate/Optimise: GridSearchCV, K-fold

Feature Eng: RFECV
Models: All Ensemble Class from Sklearn + GaussianNB
Validate/Optimise: GridSearchCV, K-fold

Re-sampling: SMOTE
Models: LogR, RandForest, GaussianNB, Votting
Validate/Optimise: GridSearchCV, K-fold

Feature Eng: RFECV
Models: LogR, KNN & RandForest
Validate/Optimise: GridSearchCV

Models: NeuralNets (MLPClassifier)
Validate/Optimise: Confusion Matrix & Classification Report

Feature Eng: RFECV
Models: Multiclass LogR, RandForest & GradBoosting
Validate/Optimise: GridSearchCV, K-fold

Feature Eng: RFECV
Models: LinR, KNN & RandForest + NeuralNets
Validate/Optimise: GridSearchCV, bias vs var

Feature Eng: heatmap, SelectKBest & RFECV
Models: LinR, KNN, RandForest & GradBoosting
Validate/Optimise: GridSearchCV, K-fold

Feature Eng: heatmap & RFECV
Models: LinR, RandForest & GradBoosting
Validate/Optimise: LinR P-values, GridSearchCV, K-fold

Models: Convolutional Neural Networks
Validate/Optimise: K-fold

Models: Keras Sequential models and Dense layers

Models: NMF, LatentDirichletAllocation, TruncatedSVD
Visualization: pyLDAvis & WordCloud

Models: LatentDirichletAllocation
Visualization: pyLDAvis

Models: Naive Bayes, LinR and RandForest + bag-of-words

Models: MiniBatchKMeans, DBSCAN
Validate/Optimise: Elbow Curve, train_test_split

Models: K-means Clustering