Training and evaluation

Training is the process of teaching a model to recognize patterns by providing it with a large amount of data and feedback, so it learns to make accurate predictions or decisions. Evaluation involves testing the trained model on separate, unseen data to assess how well it performs outside of its training environment. This helps ensure the model can generalize its knowledge to new situations and maintains accuracy and reliability before being used in real-world applications.