This project is focusing on the effect of normalization, including standardizing, scaling and more, on the training and inference of machine learning models. A lot of focus in machine learning is on models and less so on data and how to treat it. In this project we will focus on the impact of data on model training.
Improve models' performance by running grid search before training - make it optional.