Training and Testing the data | Training vs Testing the data | Why Training and Testing in ML

Training and testing data are essential steps in machine learning, each serving a distinct purpose in model development. Training data is used to teach the model patterns and relationships within the dataset, enabling it to make predictions. In contrast, testing data evaluates the model's performance and generalization to unseen data. This dual approach ensures that the model is both accurate and robust.