Machine Learning (ML) is a subfield of Artificial Intelligence (AI), in simple words, it is defined as the capability of a machine to imitate intelligent human behavior. Arthur Samuel coined the term ML in the year 1959. He was a pioneer in AI, computer gaming, and ML. Broadly, ML is the study of making machines more human-like in their behavior and decisions by giving them the ability to learn and develop their own programs. This is done with minimum human intervention, i.e., no explicit programming. Now you may wonder, how ML differs from traditional programming? A well-written and tested program will be feed into a machine to generate output. When it comes to ML, input data along with the output is fed into the machine during the learning phase, and it works out a program for itself. The performance of an ML system can be improved through training and by exposing the algorithm to more data. ML is one of the most exciting technologies that one would have ever come across. ML is actively being used today in many places. Here are few examples where ML is used like internet search engines, email filters to sort out spam, websites to make personalized recommendations, banking software to detect unusual transactions, and lots of apps on smartphones that use ML technology such as voice recognition.

The ML technology can provide great support in our future developments that will have a significant impact on our society. For example, ML could provide us with readily available ‘personal assistants’ to help manage our lives, it could dramatically improve the transport system through the use of autonomous vehicles; and the healthcare system, by improving disease diagnoses or personalizing treatment. ML could also be used for security applications, such as analyzing email communications and more.