Machine learning (ML) is a part of an artificial intelligence developed for the technological development of human knowledge. ML provisions devices to dynamically handle any situation through analysis, self-training, observation, and experience, which makes continuous improvement of decisions in subsequent scenarios. ML is ambiguous with data mining in databases for knowledge engineering. It is focused on predictions based on known facts learned from training data, while data mining focuses on the discovery of unknown facts. Data mining uses many ML methods, whereas ML uses unsupervised learning to improve the user’s accuracy. Machine learning and statistics are very closely tied domains.
In computational learning theory, a computation is considered feasible if it can be done in polynomial time. Some classes of functions can be learned in polynomial time and others cannot. The approaches of ML are decision tree learning, association rule learning, artificial neural networks...