Question

Consider a potential business problem that would require a computer program solution. How could an algorithm be used to solve a problem that a business may encounter?

Answer 1

`Hey,

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To decide, you need to think about the problem to be solved and the available data, and ask questions about feasibility, intuition, and expectations.

Start by distinguishing between automation problems and learning problems. Machine learning can help automate your processes, but not all automation problems require learning.

Automation without learning is appropriate when the problem is relatively straightforward. These are the kinds of tasks where you have a clear, predefined sequence of steps that is currently being executed by a human, but that could conceivably be transitioned to a machine. This sort of automation has been happening in businesses for decades. Screening incoming data from an outside data provider for well-defined potential errors is an example of a problem ready for automation. (For example, hedge funds automatically filtering out bad data in the form of a negative value for trading volume, which can’t be negative.) On the other hand, encoding human language into a structured dataset is something that is just a tad too ambitious for a straightforward set of rules.

For the second type of problems, standard automation is not enough – they require learning from data. And we now venture into the arena of machine learning. Machine learning, at its core, is a set of statistical methods meant to find patterns of predictability in datasets. These methods are great at determining how certain features of the data are related to the outcomes you are interested in.

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