Feature scaling

Data will always give us the best results if we treat it in the right way that's why it has a better idea than dealing with it directly. In this article, we will discuss feature scaling, The most commonly feature scaling methods and when to use them. Feature scaling is a significant stage in the pre-processing of data before developing a machine learning model. The difference between a bad and a good machine learning model can be determined by scaling. Machine learning algorithms deals with numbers only, and if there is a significant difference in range, such as a few ranging in the hundreds against a few ranging in the tens, it assumes that greater ranging numbers have some form of superiority.