Monitoring

Monitoring of ML models can be a difficult task. SWE provides an OOB solution for monitoring your models. By using SWE you can simply create monitoring metrics and policies that will alert you when something is wrong or when anomalies occur in your data or data pipeline.

Monitoring machine learning models can often be a complex and intricate task. It requires a high level of understanding of the underlying algorithms, as well as a keen eye for anomalies and inconsistencies in the data. SWE provides an Out-of-the-box solution for the monitoring of your models. This solution is designed to streamline the process of keeping tabs on your models and making sure they are performing as expected.

In addition to creating monitoring metrics, the SWE solution also allows you to establish policies. These policies act as guidelines or rules that trigger alerts when something is not right. Whether it's a sudden drop in the accuracy of your model, an unexpected increase in the error rate, or anomalies occurring in your data or data pipeline, these policies will send you an alert. This proactive approach not only helps in identifying issues at an early stage but also allows you to take timely corrective actions to ensure the optimal performance of your models.