How is machine learning defined?

Machine learning is accurately defined as a subset of artificial intelligence focused on enabling systems to learn from data and improve their performance over time without being explicitly programmed for each specific task. This definition captures the essence of machine learning, which involves the development of algorithms and statistical models that allow computers to analyze and make predictions or decisions based on data inputs.

This area of study is distinct from methods like data visualization, which is concerned with representing data graphically for ease of understanding, or programming systems in a conventional sense, where explicit instructions are defined for every action the system must take. While machine learning does involve algorithms for data analysis, its fundamental characteristic is the ability to adapt and learn from new data, which is a hallmark of artificial intelligence. Thus, defining machine learning as a subset of AI underscores its role in fostering systems that can independently improve and adapt their functionality through experience.