Loading the modeling, Creating a data frame, Visualization of the model, Separation of Dependent and Independent Variables Feature Scaling and Normalization, Result Visualization, Finding the best algorithm by reducing the number of columns with PCA, Comparison of normal dataset and PCA dataset using KNN,SVC,KMeans and Logistic Regression models
Loading the modeling, Creating a data frame, Visualization of the model, Separation of Dependent and Independent Variables Feature Scaling and Normalization, Result Visualization, Finding the best algorithm by reducing the number of columns with PCA, Comparison of normal dataset and PCA dataset using KNN,SVC,KMeans and Logistic Regression models