Alerts and automated retraining are essential components in the realm of machine learning and data science. Alerts serve as notifications that inform data scientists and engineers when a model’s performance deviates from expected standards, often due to data drift or changes in underlying patterns. Automated retraining, on the other hand, is the process of updating machine learning models without manual intervention, triggered by specific performance metrics. Together, these mechanisms ensure that models remain accurate and relevant over time, optimizing performance and reducing the risk of outdated predictions in dynamic environments.