The term machine learning was coined in 1959 by Arthur Samuel, an IBM employee and pioneer in the field of
Although … 展开

As a scientific endeavor, machine learning grew out of the quest for artificial intelligence (AI). In the early days of AI as an academic discipline, some researchers were interested in having machines learn from data. They … 展开

A core objective of a learner is to generalize from its experience. Generalization in this context is the ability of a learning machine to perform accurately on new, unseen examples/tasks after having experienc… 展开

Machine learning approaches are traditionally divided into three broad categories, which correspond to learning paradigms, depending on the nature of the "signal" or "feedback" available to the learning system: … 展开

A machine learning model is a type of mathematical model that, after being "trained" on a given dataset, can be used to make predictions or classifications on new data. During training, a learning algorithm iteratively adjust… 展开

There are many applications for machine learning, including:
• Agriculture
• Anatomy
• Adaptive website
• Affective computing… 展开