Machine learning (ML) and data science are often mentioned in the same breath – and for good reason. The two complement each other. However, understanding how they work – and work together – is important.
Sometimes, data science is enough. “It is difficult to distinctly separate data science and ML since boundaries are blurry. At the end of the day, most of the algorithms use statistical techniques,” says Anil Vijayan, Vice President at Everest Group. “Not every problem requires AI to solve though. In many cases, using “traditional” data science may not just suffice, but also be more efficient.”
