Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.
To ensure the long-term success of machine learning models, it's essential to understand how to effectively monitor them in production. As machine learning becomes more widely adopted in the business world, post-deployment data science is emerging as an important field. This course covers all the essential concepts related to monitoring machine learning systems in production, in order to maintain business value, reduce the risk of failure, and increase visibility.
To ensure the long-term success of machine learning models, it's essential to understand how to effectively monitor them in production. As machine learning becomes more widely adopted in the business world, post-deployment data science is emerging as an important field. This course covers all the essential concepts related to monitoring machine learning systems in production, in order to maintain business value, reduce the risk of failure, and increase visibility.
