Arthur Samuel (1901-1990) was a pioneer of artificial intelligence research. From 1949 through the late 1960s, he did the best work in making computers learn from their experience. His vehicle for this work was the game of checkers. Programs for playing games often fill the role in artificial intelligence research that the fruit fly Drosophila plays in genetics. Drosophilae are convenient for genetics because they breed fast and are cheap to keep, and games are convenient for artificial intelligence because it is easy to compare a computer's performance on games with that of a person.
This big data discipline of artificial intelligence gives systems the freedom to automatically gain information and improve from experience without manual programming. Machine learning is literally just that – "letting the machine learn". The definition of machine learning is "the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model of sample data, known as'training data', in order to make predictions or decisions without being explicitly programmed to perform the task".
Programmed by Arthur Samuel, this big data discipline of artificial intelligence replaces the tedious task of trying to understand the problem well enough to be able to write a program, which can take much longer or be virtually impossible. Techopedia defines the discipline of machine learning as "an artificial intelligence (AI) discipline geared toward the technological development of human knowledge. Machine learning allows computers to handle new situations via analysis, self-training, observation and experience. Machine learning facilitates the continuous advancement of computing through exposure to new scenarios, testing and adaptation, while employing pattern and trend detection for improved decisions in subsequent (though not identical) situations." In 1959, IBM employee Arthur Samuel wanted to teach a computer to play checkers.
Machine Learning is a form of Artificial Intelligence (AI) which allows computers to learn by way of observation and experience, rather than rigid pre-programming. Machine Learning uses computer programs that are capable of growth and change as they process new data. Using algorithms, Machine Learning allows computers to develop habitual responses based on the repeated behaviors and actions of the person using the computer. The concept of learning repeated behaviors is important. As models are presented with new data, they adapt, learning from earlier experiences to provide reliable, consistent results and responses.