Change is the only constant in life - Heraclitus quote is so relevant in the Machine Learning world. The ML models that are running in the production need to be monitored. Why? Because data can change in time, leading to wrong predictions. The change in data distribution is so-called a data drift. I will show you how to build a dashboard for data drift detection in Python. I will use Evidently Python package for detecting data drift and building a dashboard in the Jupyter Notebook. The dashboard notebook will be published as a web application with the Mercury framework.

Would you like to build a data dashboard in 9 lines of Python code? I will show you how to create a dashboard in Python with Jupyter Notebook. The dashboard will present information about stock for selected ticker (data table and chart). The notebook will be published as a web application. I will use an open-source Mercury framework to convert Python notebook to interactive web application.

Do you need to monitor data from multiple sources and act based on their values? If you answered yes, then it means that you need a dashboard. I will show you how to create a dashboard in Python. It will automatically update the values in the dashboard and send email notifications based on monitored values. The dashboard will be deployed to the Amazon AWS cloud service.