Finding parameters with extreme values (classification with scikit-learn)
If by "parameters" you mean features (called "Data Fields" at Kaggle), then, yes, you can log-scale those. To visualize them you can just use histograms.
To do it for all features in python, for example, you can put your data in pandas DataFrame (let us call it "data") and then use data.hist()
This has nothing to do with the regularization in any model.

If by "parameters" you mean the coefficients obtained after fitting the logistic regression, then one uses regularization. This has, however, is not directly related to log-transform. How you list/visualize your coefficients depends on the programming tool you use for logistic regression (or other model)