Training the model

• After identifying predictors and selecting a modeling technique, the next step is to proceed with model training.
• During this phase, the model is presented with data from which it can learn and derive pattern.
• Common modeling techniques have industry-ready implementations in various programming languages.
• Python, for example, offers libraries with easy-to-use functions for model training.
• Model Validation involves assessing the model’s performance after training by testing its ability to make accurate predictions on new, unseen data.