You are leading a machine learning project aimed at predicting housing prices. The dataset includes features such as square footage (ranging from 500 to 10,000), number of bedrooms (1 to 5), and age of the property (1 to 100 years). During the training phase of your Neural Network model, you observe that the gradient optimization is struggling to converge, likely due to the varying scales of the features. Considering the need for a solution that ensures numerical stability and enhances convergence without compromising the integrity of the data, what is the most effective action to take? Choose one correct option.