Standardization is one of the most useful transformations you can apply to your dataset. What is even more important is that many models, especially regularized ones, require the data to be standardized in order to function properly. In this article, you will learn everything you need to know about standardization. You will learn why it works, when you should use it, and how you can do so with just a few lines of code.
If you are just starting out in machine learning and building your first real models, you will have to split your dataset into a train set as well as a test set. But what benefits does this splitting yield? How can you split your dataset optimally? In this article, we will go through these questions and explore why splitting your dataset makes sense and how you can split your dataset properly.