In the first post of part four, we introduced you to a simplistic scenario illustrating the role machine learning plays in the data science workflow. As a fleet manager responsible for a number of delivery trucks, we showed how machine learning algorithms can help you determine whether a delivery will be successful, in real time.
When dealing with large quantities of industrial data, there are many different ways to combine data inputs to come up with a mathematical understanding of a particular problem. Machine learning algorithms encapsulate that understanding into what is called a data science model. In the above example, the data science model outputs predictions to the fleet managers, enabling them to take action to change the outcomes of the business.
In the second video of part four, Manny B. explains how machine learning algorithms create data science models with the help of "Mr. Roboto”:
