Data science versus machine learning

Data science is the science of using data to solve a measurable real-world problem using a series of experiments to perform an in-depth analysis of cause and effect. As in any science experiment, one starts with a question, formulates a hypothesis, conducts several experiments to establish actual evidence, interprets the results dispassionately, and delivers the results, also known as insights, to the business stakeholders who started the chain by asking a question, as shown in the following diagram.

Figure 9.1 – The "science" of data science

There are a lot of steps! This is because data science requires interdisciplinary skills from applied statistics as well as domain knowledge from areas other than software engineering. The core ingredient is data, and there is a whole range of skills that data scientists need to manage and transform it. 

Python and R are popular choices for data science, but...