required to be able to understand and develop the ML models and integrate them into the production or analytic or back-end applications in an organization. Presenting data in a graphical format makes it much easier to see and understand what is happening with the data. Data visualization applies to all phases of the data science process. When data are inspected in tabular form, it is easy to miss things such as outliers or trends in distributions or subtle changes in the data through time. However, when data are presented in the correct graphical form, these aspects of the data can pop out.
