Machine learning dates back to centuries. It was born from the theory that computers can learn without being programmed to perform specific tasks. The iterative aspect of ML is essential as the machines need to adapt themselves to new data always. They need to learn from the historical data, optimize for better computations, and also generalize themselves to provide proper results.
We all are aware of rule-based systems, where we have a set of predefined conditions for a machine to execute and provide the results. How great will it be when machines learn these patterns by themselves, deliver the results, and explain the rules that it discovered; this is ML. It is a broader term used for various methods and algorithms that are used by machines to learn from the data. As a branch of artificial intelligence (AI), the ML algorithms are quite often used to discover...
