Ml-2
*With textual data we cannot perform mathematical function that's why we are converting the textual data into dumy variable *visiulisation gives you correlation but remember corelation does not means causation causation is an impact or effect * We are learning machine learning because machine learning gives us causation, cofficient is actually a causation * causation is actually a deep level of correlation * the differcenc between the actual and predicted is called an error * in statsmodel ols (ordinary least square) class give us a method called summary , with summary we can do the statistical analysis of data sets * Signinficance level is considered as 0.05 * if p value for certain colum is greater than 0.05 we will remove that coloum because that colum is garbage that is unimportant variable *R 2 tells us how point is closed to the line . but if number of variable increase r2 will also increase , but as we know profit does not depand upon phone number(unimportant variable) , so...