Machine Learning Algorithms - What, Why, and How? - KDnuggets

Before machine learning became mainstream, programmers wrote rules derived from a function of their domain knowledge, observation of some hand-picked instances, and the business requirement to perform a particular task. But this legacy way of delivering business results suffered some evident constraints. Let's take an example of a fraud detection case. The programmer would write rules that if the transaction amount is above $10K, transaction location is X, and it is made from a particular type, i.e., wire transfer, then it is flagged as a potentially fraudulent transaction. This could work like a charm for some time until the bad actors find an intelligent way to commit fraud.