Category Machine Leaning Articles

S21L01 -Bayes theorem

S21L02 – Likelihood vs probability, normal distribution

S21L03 -Multinomial naive bayes

S21L04 – The log scale

S21L05 – Gaussian naive bayes

S21L06 – Gaussian naive bayes under Python

S22L01 – Euler_s number

S22L02 – Balanced vs imbalnced data

S23L01 -SVM getting started with 1D data

S23L02 -SVM, mapping higher dimension

S23L03 -SVM, in 2D space

S23L04 -SVM implementation using python

S24L01 -Decision Tree and Random forest

S25L01 -AdaBoost and XGBoost classifier

S26L01 -The accuracy, not so accurate

S26L02 -Confusion matrix

S26L03 -Accuracy, precision, recall, Specificity, F1 Score

S26L04 -Confusion Matrix 3D

S27L01 – Classification model master template

S27L02 -Classification model master template

S28L01 -Updated template with GridSearchCV

S28L02 -RandomizedSearchCV

S29L01 -ROC, AUC and PR curve background

S29L02 -ROC, AUC – Evaluating best model

S29L03 – ROC, AUC – Calculating the optimal threshold (Youdens method)