http://scikit-learn.org/stable/auto_examples/preprocessing/plot_all_scaling.html

https://stackoverflow.com/questions/39120942/difference-between-standardscaler-and-normalizer-in-sklearn-preprocessing

https://machinelearningmastery.com/how-to-scale-data-for-long-short-term-memory-networks-in-python/

https://jmetzen.github.io/2015-01-29/ml_advice.html

https://www.kaggle.com/rtatman/data-cleaning-challenge-scale-and-normalize-data

Mohamed AbdElAziz Khamis

I have read almost all of them before. There are convincing arguments in favor of both scaling methods. However, I can't find any relevant argument comparing the application of these methods for scaling features that deal with currency (transaction amount, for instance) neither in the literature, nor through the Web.

http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.StandardScaler.html

http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.RobustScaler.html

http://scikit-learn.org/stable/modules/preprocessing.html

https://machinelearningmastery.com/rescaling-data-for-machine-learning-in-python-with-scikit-learn/