What Is Machine Learning?

Machine learning is a branch of artificial intelligence (AI) and computer science that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. It focuses on the use of data and algorithms (procedures) to imitate the way that humans learn, gradually improving its accuracy.

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Arthur Samuel, an IBM executive, is credited for coining the term machine learning with his research around the game of checkers. He defined machine learning as a field of study that gives computers the capability to learn without being explicitly programmed. Robert Nealey, a checkers master, played the game on an IBM computer in 1962, and he lost to the computer. Compared to today’s computing power this feat seems trivial, but it was a major milestone in the field of artificial intelligence at that time. Some examples of machine learning can be seen in the way Amazon or Netflix recommends products, books, and movies based on what users have purchased, searched, or viewed in the past.

How ML works - Machine Learning makes computers 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 and without explicit programming. The learning process is automatic and upgraded based on the experiences of the machines throughout the process.

This requires good quality data to be fed to the machines and different algorithms build ML models to train the machines on this data. The choice of algorithm depends on the type of data at hand, and the type of activity that needs to be automated. Most company websites now have artificial intelligence-based chat robots that help users with common support activities.

Isn’t this traditional programming?