Learning, like intelligence, covers such a broad range of processes that it is difficult to define precisely. A dictionary definition includes phrases such as “to gain knowledge or understanding of. or skill in, by study, instruction, or experience” and “modification of a behavioural tendency by experience”.
Ever since computers were invented, we have wondered whether they might be made to learn. If we could understand how to program them to learn-to improve automatically with experience-the impact would be dramatic. Imagine computers learning from medical records which treatments are most effective for new diseases, houses learning from experience to optimize energy costs based on the particular usage patterns of their occupants, or personal software assistants learning the evolving interests of their users in order to highlight especially relevant stories from the online morning newspaper. A successful understanding of how to make computers learn would open up many new uses of computers and new levels of competence and customization. And a detailed understanding of information processing algorithms for machine learning might lead to a better understanding of human learning abilities (and disabilities) as well.
We do not yet know how to make computers learn nearly as well as people learn. However, algorithms have been invented that are effective for certain types of learning tasks, and a theoretical understanding of learning is beginning to emerge. Many practical computer programs have been developed to exhibit useful types of learning, and significant commercial applications have begun to appear. For problems such as speech recognition, algorithms based on machine learning outperforms all other approaches that have been attempted to date. In the field known as data mining; machine learning algorithms are being used routinely to discover valuable knowledge from large commercial databases containing equipment maintenance records, loan applications, financial transactions, medical records, and the like. As our understanding of computers continues to mature, it seems inevitable that machine learning will play an increasingly central role in computer science and computer technology.
Sources of Information:
INTRODUCTION TO MACHINE LEARNING by Nils J. Nilsson.
MACHINE LEARNING by Tom M. Mitchell.