The Difference Between Training and Testing Data in Machine Learning - KDnuggets

When building a predictive model, the quality of the results depends on the data you use. If you are using not enough or wrong data, your model will not be able to make realistic predictions and will lead you in the wrong direction. To avoid this, you need to understand the difference between training and testing data in machine learning. Without further ado, let's dive in. Let's say you want to create a model based on some database.