What do you do with highly correlated features? When the VIF is high in particular?

I am preparing a dataset for a classification task at work, as you can see, I have 13 features with multicollinearity, also, I could not infer any good decisions about what to do given the correlation matrix.

What do you think I should do here? I have a total of 60 features, I cleaned the data and checked for duplicates and outliers, standardized the data and everything, now it’s a matter of feature selection I think?

Could really use some …

classification correlation datascience dataset decisions features good matrix multicollinearity think vif work